{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DS1000E Rigol Waveform Examples\n",
    "\n",
    "**Scott Prahl**\n",
    "\n",
    "**March 2021**\n",
    "\n",
    "This notebook illustrates shows how to extract signals from a `.wfm` file created by a the Rigol DS1000E scope.  It also validates that the process works by comparing with `.csv` and screenshots.\n",
    "\n",
    "Two different `.wfm` files are examined one for the DS1052E scope and one for the DS1102E scope.  The accompanying `.csv` files seem to have t=0 in the zero in the center of the waveform. \n",
    "\n",
    "*If RigolWFM is not installed, uncomment the following cell (i.e., delete the #) and run (shift-enter)*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install --user RigolWFM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "try:\n",
    "    import RigolWFM.wfm as rigol\n",
    "except ModuleNotFoundError:\n",
    "    print('RigolWFM not installed. To install, uncomment and run the cell above.')\n",
    "    print('Once installation is successful, rerun this cell again.')\n",
    "\n",
    "repo = \"https://github.com/scottprahl/RigolWFM/raw/master/wfm/\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A list of Rigol scopes in the DS1000E family is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['E', '1000E', 'DS1000E', 'DS1102E', 'DS1052E']\n"
     ]
    }
   ],
   "source": [
    "print(rigol.DS1000E_scopes[:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DS1052E\n",
    "\n",
    "We will start with a `.wfm` file from a Rigol DS1052E scope. This test file accompanies [wfm_view.exe](http://meteleskublesku.cz/wfm_view/) a freeware program from <http://www.hakasoft.com.au>.  \n",
    "The waveform looks like\n",
    "\n",
    "<img src=\"https://github.com/scottprahl/RigolWFM/raw/master/wfm/DS1052E.png\" width=\"50%\">\n",
    "\n",
    "Now let's look at plot of the data from the corresponding `.csv` file created by [wfm_view.exe](http://meteleskublesku.cz/wfm_view/)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "csv_filename_52 = \"https://raw.githubusercontent.com/scottprahl/RigolWFM/master/wfm/DS1052E.csv\"\n",
    "csv_data = np.genfromtxt(csv_filename_52, delimiter=',', skip_header=19, skip_footer=1, encoding='latin1').T\n",
    "\n",
    "center_time = csv_data[0][-1]*1e6/2\n",
    "\n",
    "plt.subplot(211)\n",
    "plt.plot(csv_data[0]*1e6,csv_data[1], color='green')\n",
    "plt.title(\"DS1052E from .csv file\")\n",
    "plt.ylabel(\"Volts (V)\")\n",
    "plt.xlim(center_time-0.6,center_time+0.6)\n",
    "plt.xticks([])\n",
    "\n",
    "plt.subplot(212)\n",
    "plt.plot(csv_data[0]*1e6,csv_data[2], color='red')\n",
    "plt.xlabel(\"Time (µs)\")\n",
    "plt.ylabel(\"Volts (V)\")\n",
    "plt.xlim(center_time-0.6,center_time+0.6)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now for the `.wfm` data\n",
    "\n",
    "First a textual description."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "downloading 'https://github.com/scottprahl/RigolWFM/raw/master/wfm/DS1052E.wfm?raw=true'\n",
      "    General:\n",
      "        File Model   = wfm1000e\n",
      "        User Model   = 1000E\n",
      "        Parser Model = wfm1000e\n",
      "        Firmware     = unknown\n",
      "        Filename     = DS1052E.wfm\n",
      "        Channels     = [1, 2]\n",
      "\n",
      "     Channel 1:\n",
      "         Coupling =  unknown\n",
      "            Scale =     1.00  V/div\n",
      "           Offset =     2.00  V\n",
      "            Probe =      10X\n",
      "         Inverted =    False\n",
      "\n",
      "        Time Base =  100.000 ns/div\n",
      "           Offset =    0.000  s\n",
      "            Delta =    2.000 ns/point\n",
      "           Points =     8188\n",
      "\n",
      "         Count    = [        1,        2,        3  ...      8187,     8188]\n",
      "           Raw    = [       76,       76,       76  ...        76,       76]\n",
      "           Times  = [-8.188 µs,-8.186 µs,-8.184 µs  ...  8.186 µs, 8.188 µs]\n",
      "           Volts  = [ 40.00 mV, 40.00 mV, 40.00 mV  ...  40.00 mV, 40.00 mV]\n",
      "\n",
      "     Channel 2:\n",
      "         Coupling =  unknown\n",
      "            Scale =     2.00  V/div\n",
      "           Offset =    -6.00  V\n",
      "            Probe =       1X\n",
      "         Inverted =    False\n",
      "\n",
      "        Time Base =  100.000 ns/div\n",
      "           Offset =    0.000  s\n",
      "            Delta =    2.000 ns/point\n",
      "           Points =     8188\n",
      "\n",
      "         Count    = [        1,        2,        3  ...      8187,     8188]\n",
      "           Raw    = [      203,      203,      203  ...       138,      138]\n",
      "           Times  = [-8.188 µs,-8.186 µs,-8.184 µs  ...  8.186 µs, 8.188 µs]\n",
      "           Volts  = [-80.00 mV,-80.00 mV,-80.00 mV  ...   5.12  V,  5.12  V]\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# raw=true is needed because this is a binary file\n",
    "wfm_url = \"https://github.com/scottprahl/RigolWFM/raw/master/wfm/DS1052E.wfm\" + \"?raw=true\"  \n",
    "w = rigol.Wfm.from_url(wfm_url, '1000E')\n",
    "\n",
    "description = w.describe()\n",
    "print(description)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEWCAYAAAB8LwAVAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAABS0klEQVR4nO2deXxU1fXAvyd7yAYJBAyrKCIqKoIo4FYV677VVq1aW/1Jaxe1LtStFlvXYm217vu+r1hxAQEXFFkVBGQPSwKELfuenN8fd14ySWYmk8xMXia5389nPvPmLfedN/e+e+45995zRVWxWCwWi6U5MW4LYLFYLJbOiVUQFovFYvGJVRAWi8Vi8YlVEBaLxWLxiVUQFovFYvGJVRAWi8Vi8YlVEBaLD8TwrIjsEZH5bssTLCIyQUTWiEipiJwdhvTOEZHNnvRGichyETnOc2yKiLwU6j0snRerICxtQkRyRaRCREpEpFBEvhaR34lIjNc5A0TkbRHZKSJFIvKDiPza6/gTIrJKROq993sd/7OIbBORYhF5RkQSfdy/1PP51OvYpSKyyHPdFhH5p4jEBbi2VEQe8vOoRwETgQGqOjakP61j+TvwkKqmqup7YUjvPuCPnvSWqOqBqjonDOlaogCrICzt4QxVTQMGA/cAfwGe9jr+IrDZczwLuATY7nX8e+D3wOLmCYvIT4EbgRM81w8Fbvdx/1TP5ySv/T2Aa4DewBGeNK4PcG2qqv7RzzMOBnJVtczXQW/F08kYDCzvxOlZogirICztRlWLVHUacD5wqYgc5Dl0OPCcqpapaq2n5fmR13UPq+pnQKWPZC8FnlbV5aq6B/gH8Osg5XlUVb9U1WpVzQNeBia09blE5HLgKWCcx8q4XUSO81glfxGRbcCzIpIoIv8RkXzP5z+OteN1/mQRKRCRrSJytoicKiKrRWS3iNwcpDy/EZEPvH6vEZE3vX5vFpFDRWQdRqF+4JE7UUTmiMgdHkuvVEQ+EJEsEXnZY2ktEJEhPu6ZKCKlQCzwvSdtxwo70Y+cR3ruUygi3zuuKEv0YhWEJWRUdT6wBTjas2se8LCIXCAig9qY3IEYC8Phe6CviGR57XtZRHaIyKcickiAtI6hHa1fVX0a+B3wjcfK+JvnUD8gE9OqngTcAhwJHAocAowFbvVKqh+QBPQHbgOeBC4GRmP+q7+KyN5BiPQ5cLSIxIhIDpAAjAMQkaFAKrBUVfcBNtFoJVV5rr8AY8X1B/YBvgGe9TzLSuBvNENVq1Q11fPzEE/afhGR/sCHwB2edK8H3haRPkE8n6WTYhWEJVzkYyoGgJ8DXwJ/BTaIyHcicniQ6aQCRV6/ne00z/dFwBBMJT0b+EREejZPREQuA8ZgfOjevOdp4TqfK4KUC6Ae+Jun8qzwyPJ3VS1Q1R0YV9glXufXAHeqag3wGsb19YCqlqjqcmAFRrEERFXXAyUYRXQM8AmQLyL7A8cCX6pqfYAknlXVdapaBHwErFPVmapaC7wJjGrDf+CPi4HpqjpdVetVdQawEDg1DGlbXMIqCEu46A/sBlDVPap6o6oeCPQFvsNUzBJEOqVAutdvZ7vEk/ZcVa1Q1XJVvRsopNFyAUDM6J27gVNUdWez9M9W1Z5enyfb8Iw7VNXbLZYDbPT6vdGzz2GXqtZ5tis83959MRUYhRgMnwPHYRTE58AcjHI41vM7EM3v2V4ZAjEY+Lm38sV09O8VhrQtLmEVhCVkPNZBf+Cr5sc8FfR9mIozs/lxHyynaav6EGC7qu7yc74CDYpHRE7GuHLOUNVlQT1A8DQPfZyPqRgdBnn2RQJHQRzt2f6c4BVER7AZeLGZ8k1R1XvcFszSfqyCsLQbEUkXkdMx7pOXnApZRO4VkYNEJE5E0oArgbVOJS8iCSKShKnY40UkSRqHyb4AXC4iB3hcR7cCz3muGyRmnH+C55obMG6buZ7jx2M6pn/m6ReJNK8Ct4pIHxHpjelniNS8gM+BnwDJqroF48I7GTNKbEmE7tkWXgLOEJGfikisJ3+OE5EBbgtmaT9WQVjawwciUoJpNd4C3A/8xut4D+BdjPtnPaaVfabX8U8xro3xwBOe7WMAVPVj4J+Y/oVNGLeN04maBjwK7AHyMBXkKV7WxV+BDGC61zyHhtFTXrJ7z4N4N4T/4Q6Mn30psAwzbPeOENJrQERu9pZdVVdj3G9fen4XY/7buV5uLNdQ1c3AWcDNwA5M2bgBW8dENWIXDLJYLBaLL6x2t1gsFotPrIKwWCwWi0+sgrBYLBaLT6yCsFgsFotPOmvAMZ/07t1bhwwZ4rYYFovFElUsWrRop6q2OeyJawpCRAZixrz3xUxAekJVHwh0zZAhQ1i4cGFHiGexWCxdBhHZ2PpZLXHTgqgFrlPVxZ7JVItEZIaqrnBRJovFYrF4cK0PQlW3qupiz3YJJqpkf7fksVgsFktTOkUntSce/SjgWx/HJonIQhFZuGPHjg6XLdz8UPADY58cy/bS7a2fbOn2XPfJddz5xZ1ui2GJAtbtXscRTx3BluItYUvTdQUhIqnA28A1nvABTVDVJ1R1jKqO6dMn+kPL3zb7NhbkL+DFpS+6LYqlk1Ov9dw/735unX0rdfWuR9OwdHKeWPQE8/Pm8+9v/h22NF1VECISj1EOL6vqO27K0lGs2rUKgNm5s12WxNLZWbt7bcP2t3ktjGuLpQlbS7cCsGRb+GI3uqYgPGsDPA2sVNX73ZKjI1FV1u9ZD8D8vPnYOFiWQCzZ2viiz8/riOC0lmhm8VazxPuC/AXUB1w/KnjctCAmYFbfOt6z4th3ItKlV58qrCyksraSYZnD2Fm+k01Fm9wWydKJ2Vy8GYC0hDQW5tvh3Rb/qCobCjfQK6kXpdWlrN61OizpujmK6StVFVU9WFUP9XymuyVPR+CYgKcNOw2ApduXuimOpZOTX5JPSnwKxw451pYVS0B2lu+kvKacs/Y/Cwhf3eJ6J3V3Ir/ELDZ2eH+zPPO20m1uimPp5OSX5JOTlkP/tP62rFgCsrHIzIObMHACEL66xSqIDsRREIf0NStqFpQVuCmOpZPjKIjslGx2lu+0I5ksftlYaBTEqH6jiJGYsNUtVkF0IE6mDcwYSEZihlUQloB4KwhF2VXhb1luS3dne5mZV9U/vT99evSxCiIaKa4qRhBSE1LJTsluyFSLxRc7ynfQp0cf+qb0BbCTKy1+KakqASA9MZ2+qX3DVrdYBdGBFFcVk5aYRozEkJ2SbS0Ii19UldLqUtIS08hOyQasS9Lin9LqUmIkhuS45LDWLVZBhEhxVTEnvXgS7658N6hzMxIzAKwF0U15eenLnPbKaVTUVAQ8r7ymnHqtJy2hUUHY8tK9KKsu45SXT+H1H15v9dyS6hJSE1IREVO3hMnatAoiRP719b+YsX4G575xLjV1NQHPLa4qJj0xHYCs5Cx2V+zuCBEtnYTymnIufvdipq+ZziMLHgl4bkm1cRmkJaaR1SMLwJaXbsZD8x/i47Ufc8HbF7TaoCitLiU1IRUIb91iFUSIeIfMWLEjcKTyoqqiBgWRmZzJnoo9djZ1N2Ld7nUN262FWnF8ymkJafRK6gXAnoo9kRPO0ulYvG1xw/b3278PeG5JdQlpCWmAqVuKqorCMurNKogQqKuvY/HWxZy878kArc529bYgeiX3oqquiorawC0DS9chtzAXgBG9R7Awf2HAxoG3BREfG09qQqq1ILoZuYW5jOg9Ami9bvG2IJwGRWFlYcgyWAURAuv2rKOspoxfHPAL0hLS+G7bdwHPb6IgbKuw27GhcAMA5444l+1l2wN2JHpbEGDKy55KW1a6Exv2bGDCwAn06dGn1bqlpKqEtERPWUn21C1hKC9WQYTAhj3mhR+WNYzBPQezpSRwHHbvTurM5EwgPJloiQ5yC3PpEd+DMTljAALG7fe2IMC89LasdB/KqsvYUb6DvXvtzYD0Aa3OjPa2IBrqljA0Pq2CCAFnevvgjMHkpOU0zJT2R3MXE9iOx+5EbmEuQ3oOoX+aWTgxUHnxZUHYstJ9cOqWvXvuHdSwVe8+CMc7EY7yYhVECGws3EhcTBw5aTmtKoh6rW8Y1w7WxdQdcRRETloO0IqCaGZBOIMaLN0Dp79qSM8hQSmIJn0Q1sXUOcgtymVA+gBiY2LZK3UvtpZs9RuHvbymHICU+BTAupi6I7mFuQzJGELf1L4I0mYLwpaV7oO3guibYmZGBxrUUFpd2mQUE1gXk+tsLNzI4IzBAOSk5VCndewo871udll1GQApCUZB9EzqCVgLortQVFnEnso9DOk5hLiYOPqm9iWvJM/v+Y4F4bQKeyb1tGWlG7FhzwYSYxPpm9qX7JRsKmsrKa0u9Xmu453wLitgLQjX2Vi0kcE9jYLo08Osl+0voFpZjUdBeCwIpy/CqQgsXRunRbh3r70BU14CBd8rqSqhR3wPYmNiAchIyqCitoLa+tqIy2pxn9wi4450wvKA/5n0jnfCcUcmxSWREJvQYIWGglUQ7aSmrob8kvwGCyIjyYxOKq4q9nl+cwsiNiaWlPgUv+dbuhbeLgMw5aWossjv+d6djuDVoAjDS2/p/Dj9VUDDTHp/FqRTJhwLAkx5CUfdYhVEO9lSvIV6rW/IROcF9pcpjnkYiUy0dH6aK4jW8r6kunFcu3M++C9flq6Ft4JwXEb+Jr45dUvzBkVxtVUQruGsJz0oYxDQ+AL7axU2dzE51xRV+W9FWroOGwo3kBKfQlayaQ22lvclVb4tCFteuj6l1aXsLN/ZaG165k75y/vm/VXgKV8BLNRgsQqinTgTV5whi6218Jq7mJxrbIuwe5BbmMvevfZGRADz0lsLwuKLhv6qnqa/KmgLoll5sS4mF3E6jJwOpFYVhB8Lwr7w3QNvlwEE4WLyY0HY8tL1ae6ObE1BdJo+CBFJEZHYkO/aBSgoKyBGYhrGHDsvc1ssiIykwK1IS9fBmQPhkJGYQWVtJdV11T7Pb25BOG4GW166Ps0VRGpCKjES49dl5KsPojULNVgCKggRiRGRX4rIhyJSAPwIbBWRFSIyVUT2DVmCKKWgrIA+PfoQI+YvbG1UkrUgui97KvZQVFXUwoIA/xW+tSC6Lxv2bGhYGQ5ARMhIzPBvQfjpg+gIC2I2sA9wE9BPVQeqajZwFDAPuFdELg5Ziihke9l2+qb2bbIvkEXgsw8iITwdSZbOTfM5EBCEgvAzzNWWl66PMwfC6a8C42by10ntrw8iHAMa4lo5fqKqtlgmTVV3A28Db4tIfMhSRCEFZQUNGt4hUKaU1ZQRFxNHQmxCw76eST0priqmtr6WuJjWssISrTR3GUDjvBlfFX5dfR3lNeVNXviUhBRiJdYG7OsGNO+vAlNe2tIHkZGYQXVdNRU1FSTHJ7dbltYsiPdE5CIRSfV3gi8F0h3YWLixISqnQyCzrqy6jB7xPZrsy07JRlF2lfufUWuJfnwpiEAWRPO4XQAxEkOflD7sKPcdysXSdfCpIBIzAjY+E2ITmjQye/foDfiP7BAsrSmIJ4DTgfUi8oaInCMiCa1c0+Upripma+lWhmcNb7I/kIKoqK1ooSAcF1VrkRot0c2Gwg1Nlg6FwGPbnVUGm7f8+qb0tWWli1NcVczuit0tFERaYprfWfQVNRUkxzUtK87s653lO0OSJ6CCUNX3VfVCYAjGpfQrYJOIPCsiE0O6cxSzetdqAIb3bpuCaJ6JrcVYsXQNnBaht085kAVRWVsJ4LO8WAXRtfFlbUIQdUuzxkSDBRGidyKoYa6qWq6qr6vqOcBJwKHAxyHdOYppUBBtsSB8+AIdBWFf+q6NM0nOm0AKoqLGtwVhFUTXp/kkOYf0hHS/gT0raytbWhDJHWBBOIhIXxH5k4jMBd4DPgEOC+nOUczmos0ADZFcHQKNPQ5kQdiXvuuiqi3mQEDgTuoGF5O1ILod/iyItMS09lkQIfZBBBw6IyJXABcCwzEuphtU9euQ7tgFyC/JJz0xvcmoAWi0IOq1vmF+hEN5TXmLTOyV1Iu4mDi2l1oXU1dlT+UeSqpLWrzwibGJxMfEt9mCKKspo6y6rMlwaUvXwVm33KngHdIT06msraSmrob42KYDR331QTgTeEO1IFobWzkOuBv4TNXPUmndkK2lWxtiMHmTnpiOopRVlzUZoggmEx23goOIkJWcZYcudmE27NkAtGwRiohfl6Q/C8KpNHZX7LYKoouyoXBDi/4qaJwlXVJd0lD5O/iyIOJj48lIzIh4H8TfVXWGP+UghgEhSRCF5Jfks1fqXi32B/Qr+xjFBEbT767sfAqiqLKIOblz3BYj6vE1Sc4hI8n30EV/FoRTMXTGBsW8LfOsJRwGcgtzW/Q/QOt9VklxSS32Z/XIivgw16ki8raI/EpEDhSRbBEZJCLHi8g/gLnAiJAkiELyS/L9WhDgPxN9TVjJTM7slPMgrvv0On7y/E+YvWG226JENd9v/54YiWFor6EtjrXVgnAURKgvfbgpqSph3NPjGPbfYQHXTbYEpqKmglU7VzEsc1iLY45HwtdQV1/9m2AszkgPc/058FdMH8TDwJfA+8D/AauA41V1RkgSRBl7KvawqWiT3xce/FsQvjIxq0fndDHNWG+y9fFFj4eUzqL8Rbz+w+vhECkq+WD1B4wfOL6FexH8T35yLIjmrUJnZEpnKy+frvsUMO6PHwp+8HveE4ueYO3utX6P19XX8cC8B8gvyQ+7jNHArA2zqKit4OR9T25xrD2Nz6zkyFsQqOoKVb1FVY9T1eGqOkpVf6mqL6lqZUh378TU1NVwxxd3sHb3WgrKCpgyZwrFVcV8vPZj6rSOU/Y9pcU1gSJulteU+1QQmcmZbX7hv93yLZe/fznLC5ZTWFnIlDlTQm4peLNq56qGBZEW5i/0eU5NXQ23fHYLv3r3V37PKasu49w3zuWSdy/xOwLjtR9e43+r/xcewV1kft58Hvz2QQDeWP4G01ZNo6y6jO+2fcfEob6nDLVqQfhxMbXF4vxy45dc8u4l3PXlXagqH67+kFeXvRr09cEwbfW0hm1/ZWHNrjX89n+/5Zdv/5K6+jqf5zy1+Cmu+eQa/jPvPz6P76nYw+QZk/2GnIgW6urruOvLu1i1cxW7K3YzZc4UdlfsZu7mucTFxHHckONaXOPdB9GcSFoQXT4AUE1dDdd8fA2/GfUb+qf156bPbmLqxKn0SenTcM6by99k7e613HT0TYB5Ac949Qy+2fINd315F31T+5JbmMvuit1U1VaRkZjB2P5jW9wr0Kpffl1MScEriAe/fZAP13zIwvyF7K7YzUdrPyIjKYMfd/7Iyp0ref083y31O764g71S9+LzjZ+zq2IXd/zkDkbtNarh+NxNc3l9+es8cPIDvPbDa9z91d0AXDnmSh5d+Ch7KvbQK7lXkzT/M+8/3PXVXSTEJlBaXco757/T5Pjmos2c+sqpDYrm7NfO5tNLPm0SDmDZ9mVc+PaFAJw1/CzuOuEuDuhzgM9neGbJM9TV13HF6Ct8Hr9x5o0s2baEzORM/v3Tf9MvtV+gv9Ivc3Ln8MGqD7jmyGu47tPrOHbwsfxh7B8ajlfUVHDVR1dx89E3N/QrlFaXcsRTRwDw7o/vNvTdvHf+ewB+n8mfgvA3Ua6tfRDPLnmWy6ZdRkp8Ci/VvMT0NdOZu3kuAAdlH8TIviP9XltWXcaNM2/kd2N+x4HZBzbsr9d6bvj0Bs4cfibr96znteWvMXfTXH458pd8sOoDFuYv5DejftMkrZKqEs549QwAFuQv4OklTzNp9KQm5+wo28FNn5n3790f3+WeE+9pMRLw6SVPM/Xrqbz6w6tcPupy/nbs31p05gI8suAR3l/1PslxyX7L1L1f3cus3Fn8bMTPWsgSLHX1ddw480bOGXEOy7YvY/ra6Txy6iP0T28MwTNt1TRW7ljJX476C2DWdDj7tbP5fOPn3DLrFvqm9GV72Xa2FG9hT+Ue9um1D4lxiS3u1aoF4cs7kZwVsvvaVQUhIicDDwCxwFOqek+g85dtX8aIh0fwq4N/xZJtSxjbfyzPfvcsI3qP4KDsg5i2ahpHDTqKB05+gFtn3UpyfDJvrXiL77d/zyMLH6FHfA/Ka8p5/vvnGZ41nJF9R/L82c9z25zb+HHnjxwx4AiO3/t4Js+YzDdbvmFk9kjSE9Op0zpyC3N5f9X79OnRhzE5Y4iNabkshr9MVFW/ndRZPbIoqymjqrbKZ8FwmLtpLld/fDX7Ze3Hof0O5Wcjfsbry1+nuq6azORM3lj+Bqt3rWZor6G8cPYLvL78dVbuWMnEfSby19l/BSBWYomRGKavmc7+vfdnQPoAHjrlIS559xI2FG5g7e61fLT2I4b0HMIfDv8DZ+9/No8ufJRFWxdx4tATAdMSPO/N81i6fSlnDj+T/mn9eeH7F7ht9m30iO/BjUfdCMAfpv+BHwp+4I6f3MGs3FnM2jCLI546ghmXzGDWhln8ZeZfyCvOA2DcgHHMyZ3DqMdH8f4F7zcxsb/e/DXXfXod87bMA+DRhY8SIzGU1ZRx7ZHXctHBF3HKy6fwxcYv2DdzX+bkzuGrTV/Rp0cfymvKGd57OIfnHE5RZREF5QV8u+VbYiSGpLgkkuKSuP+n95ORmMFtc27jsH6HcfOsmwF4b9V7rN+znk/WfcKQnkO448s7uH7c9dTU1/DUkqcoKC/g/QveJ7cwl+OfPx6A/XvvT2VtJYf0PYTvt3/P7Z/fDrScUOmQkZjhex6En07q5PhkkuOSg1IQPxT8wKT/TWJA+gA+ufgTHp7/MIu3LebIAUcyb8s8Jr44kQHpA/jFgb/gk3WfUFxVzIUHXcgby9+grKaMTUWbKK4q5qEFDzG2/1hKqkr4zaG/IatHFvfPu5/7590PwNBeQxm11yj+NPZP5BXnsXBrUwvi9jm38/cv/k691vPrQ3/N99vM/zJj/QzuOv4udlfs5jfv/4YtxVuoqK3g1qNv5Y4v72DkoyO5btx1XHzwxVzw1gUsK1jW8Nw9k3py++e388iCRxg/cDxPn/k0WT2yUFX+b9r/8cx3zzAscxgFZQUc99xxZPXIYmivoTx95tMsyFvAlM+nsHjrYrJTspm5fiaPLXyMGInh/APP58M1H1JYWUhlbSU94ntQVVdFQmwCgjC2/1geOe0R7vjiDhJiE3j1h1dZun0p931zX8PzTls1jWGZwzi036E8febTnPXaWQBcMfoKMpMzuXXWrXy+8XMO7HMgy3csb4iiMG3VNLJTsltEZ3BotQ/CR+Ozd4/elFSX+F1zJBjErU4lz8JDq4GJwBZgAXChqq7we02OKL/1n+bQXkNZv2c9e6XuxdbSrS2OHzfkuBYjcxwzTBCG9x7OI6c+wvEvHM/k8ZO5d+K9Defd9/V93DDjBgBunHAjd594d4v091TsIfOfpgV7zZHXNOyvrK0k+c5k7jr+rgYrxeGxhY9x5YdXkn9tPnultRwZBVBbX8thjx9GYWUhK/6wosX8i4qaCq7/9Hpyi3KZvmZ6E9MyKS6JqtoqFOXaI69l7ua5fJv3bcO1SXFJDS1WgLH9xzLtgmn0Te3b8Dx3n3B3Q8V/9UdX8+B840rZcPUGdpbv5PAnD2+4fuEVC7n202v5YuMXTJ04levHX4+qcvNnN3PP3HtauNRmXDKDE4eeyBcbv+CMV8+gqraKpLgkYiSGlIQUdlfsJiMxg/EDx6MoNXU1zN08tyEN72dd+YeVLNu+jBeXvkhtfS0frf3I5/8JMCZnDFuKt1BcVUxNXQ019SbmZIzEUO8ZtHfUoKP4atNXxMXEUVtfS3xMPElxSQ1m/rQLpvHYoseYvmY6D5z8AFcdcVVD+oc9fhhLti1BEMpuLvP5At808yb+9c2/qLq1qklLeMqcKdz++e3U3VbXohU94P4BnLTPSTxz1jN+n23Guhmc/PLJ9Ezqyao/rmoxpv6z9Z/x4PwH+XHnjw1RARrSTx/AluItABzR/4gmZQXM/I2quioAJgycwLQLpzVYNtd/ej0PzX+I+396PzPXz+S5s58j4x7jdv31ob/m2bOe5R+f/4Pb5twGwAl7n0BWjyzeWP4GAC+c/QIXH3wxf539V9778T2W71jOQdkHNfRrHL/38fx+zO85a/+zuHza5bzw/QtN5K6rr2Nr6VZ+us9PefPnb/Ldtu+Y+vVUPlj9AWAUS3lNOQPSB3Dqvqdy6zG3cuusW9letp0VO1awbs+6Js96yr6nNJQhp+7ol9qvYblhgJHZI9kvaz96JfXiqSVPNbneuw/gqTOe4tB+h3L4k4fzx7F/5MFTHmTNrjU8vuhx+qb0ZfLMyQDcMP4G/jnxny3ytLCykF739uL+k+7nz+P+3ORY3N/j+MuEv3DnCXc22e9dt+Sk5yxS1TEtEm6FoCwIEZkAfKeqZZ71Hw4DHlDVjW29oRdjgbWqut5zj9eAswC/CqJval8uHX8pFbUVDYvzpCSkIJiX6+ajb+bhBQ+zbvc6UhNSUZRjBx/LQdkH8d6P73HDhBuYtWEWH6/9mGGZw4iLiePrzV+THJ/M+IHjueidizjtldMYmD6Qvx771yb3HpPT+N+ef9D5PuVztHxzC8JfixCaug38KYj/fvtflhUs451fvNNCOTjpPnzawwA8991zfLnxy4b/paK2gosPvpiZ62cyecJkcgtzeWrxU+Sk5XBgnwN5Z+U7jBs4joqaCnaU7+CWo29psGR6Jfdin1778OTiJ3ly8ZNsKd5CTZ2pSD/85YcM6TmEIT2H8MLZLzBvyzweWfgIN8+6mS82fsFxQ47j6iOuBsyY/7tPvJtRe43iycVPMnP9TBJiE1j6u6UNLaZjBh/D4kmLue/r+3hs0WMAnLP/OcTGxHLVEVdxUPZBDc+7qWgTjyx4hPKacsqqy8hIyiAnLYfhWcPZv/f+/PzAnwPw9OKnWbt7LWU1ZQhCXEwcsTGx9EzqyTVHXsPa3Wt5aP5D1NXX0Te1LxU1Fdx89M28uPRFSqpKuH789fxtzt8oqy7jwpEX8ubyNymvKSc1IZUH5z/Ima+dCcC/TvpXE+UAMHXiVF5Z9goj+470G245PTGdmvoaquqqmnRIV9RUkBib2EI5OOUlkAVRVl3G5dMuJy0hjffOf6+FcgA4YegJnDD0BPJL8rnnq3tITUilXusprirmqiOuYuWOlSTHJ/PTfX7KQ/MfYmTfkcxcP5PiqmLq6us4/6Dz+Tz3c246+qYmLsMxOWOoqqviD9ONS27avaZvYuLQifz7p/8GTEt6a+lWFuYvZHbubPbL2g+Ary/7mnEDxwFwx/F3cM2R1/DzN3/e0KC754R7mDxhcoMiff7s5zlq4FE8//3zzN08l0EZg9g/a3+GZQ1j8oTJxEgMRw8+mqMHH83z3z3Pjzt/pKCsgKS4JCZPmNwQBeHJM58EjEv0n3P/SVpiGqrKsKxhXDbqMt5c/iaZyZkcv/fxTP16Kqt2riI5PpkXl75IjMSwaNKiholrFx18EbmFuZRWl7K5aDM7y3eSEJvA9LXT+evsvzIwYyDZKdn84yf/AGBY1jDuO+k+vt3SqIR/NuJnPvPVee+b90HU1tdSp3V+LQgIcbKcqrb6AZYCAhwCLAH+AHwezLUB0jwP41Zyfl8CPOTjvEnAQmDhoEGDNJKc89o5yhT0nRXvtDhWW1er93x5j77/4/sB0+hxZw+97pPrmuzLK85TpqCPLXisxfkz181UpqCf537uM72SqhJNuytNT335VK2vr2/D04SHu764S5mCJvwjQf8y4y9644wbdXH+Yp/n/vTFnypTUJkiurVkq89zaupq9KFvH9Ld5bv93vPz3M/1601fh0X+SHHV9KuUKejIR0ZqdW11u9J4eP7DyhR0W8m2Jvv/NP1P2vOenj6vOe654/ToZ472m6aTX19t/KpdMoVCUWWRZt2b1fC/3DjjRp06d6rW1de1OHdB3gJlCsoU9JqPrvGZXlVtlf77m3/rW8vf8nvPsuoyfWrRU1pWXRa25wiGbzZ/ox+t+Sioc7/d8q3KFFGmoHd8fkeL43X1dXrf3Pv07RVvB0zHV91SXFmsTEGnzp3a4vxZ62cpU9DZG2YrsFDbUU8H2wdRq6oqImd5KvGnReTy9qul4FHVJzBhxxkzZkxE/WHPnPUM/3fY//kcoRQbE9vQ0RQIX/GYnPj+rVkQvpixbgYl1SVcP+56nx1ykeb68deTk5bDiD4jfHbMe/PfU/7LB6s/YN/Mff12EsfFxDXp9PXFMYOPabe8HcUtx9zCvpn7cs6Ic1qEPggW7z4r79UJ/XU6gikvP+780W+ab618i/EDxzNh0IR2yRQK6YnpfHXZV3y2/jMuPfRSn9auw+i9RvPiOS+ys3wn5x/o2yJPiE1o4qr1RY/4Hlx+WIdURU04csCRQZ87tv9Yfjv6tzy26DHO2v+sFsdjJIbrxl/XajppCS3jMfmbMwPhsSCCVRAlInITcDFwjIjEAKGuJJcHDPT6PcCzzzV6JvXk1GGnhpSGr1XlGlxMfoa5gn8FMW31NHol9eKoQUeFJFd7iY+N59JDLw3q3GFZw7h23LURlqhzkJ2SzZ+O+FNIafhbE8JfpyMEHvW2pXgLi7cu5t4T7/V5vCPYv/f+7N97/1bPExEuPrj7rFb875P/zYUjL2ziKm0r6YktI7oGcl87a0KEMpIpqGiuwPlAFXC5qm7DVOZT231XwwJgmIjs7VmE6AJgWivXdHp8DV10tLy/UUzgOxPr6uv43+r/ceqwU9vdSrV0XvyNevM3rh0aJ1aqj8ElH6wynbFnDj8zzJJaQiUpLilky9hXRNdAFkQ4Qn4Ha0H8WVUb/CuquklEDgx0QWuoaq2I/BETOjwWeEZVl4eSZmfAp4IIoOVT4lOIj4n32Sr8btt37CzfGbJVY+mc+FMQlbWV/i2I5Eyq66opqylr4cKZtnoa+2bu63dYrSW6SU9MbzHMNVDdkhiXSGpCakizqYO1IHxNBW3pqG8jqjpdVfdT1X1U9c7Wr+j8BLIgfGl5EfE7MsWZlTpuwLgISGpxG39rQvgLvgb+XZIlVSXM2jCLM/c705W+KkvkaWsfBIQebiOgghCRK0VkGTBcRJZ6fTYAy9p91y5MWy0IgD4pfSgob7kQzML8hWQmZ7YIFW3pGrTHxdSnh4kA0HzhoIX5C6muq2biPt12JeAuT7vrlhAWmWrNxfQK8BFmTYgbvfaXqGrnihjWSQg4isnPS98/rX/DrGJvFm5dyJicMbZF2EXxF5qloqaiYbXB5jhhHPKK85rMzVm1axXgP6yHJfrxFdyxNQuiX2o/n3VLsLTmYooFijHzHkq8PohIZoDrui2OlvfuRPQXfM3Be/ZqwzU1FfxQ8ANj9mrz5EdLlJAQm0BSXFKbLIgB6Wb5leblZdXOVfSI79Fw3NL1yEgyoVma1C2tWBD9UprO/G4rrVkQiwBHmubNWAVaxrzu5qQnplOv9U06EZ1M9DWKCYwFsa10W5PlBJduX0ptfW2TVqKl6+HPbeDvhc9OySYuJo68kqatwlW7VrFf1n4+Z19bugYZiRnUaV2TuG5O49Nfn1W/1H4N8Z7aQ0AFoaotlzayBMTbr9ygIFoxAwekD0BRtpVuY2CGmRridFCPzhkdaZEtLuLPbeCvrMRIDDlpOS0siO+2fWf7H7o4DS7JyqJGBRFgjhUYBVEfwmrRQTc3RORMEbnP8zm93Xfs4vjqeGzNDHT8yt4v/cKtC+nTow8D0wf6vMbSNfBrQfh54cHTZ+VlQeSX5LO1dCuj97KNia5Mw6g3rwZFQ2h4fy6mdoa9dwhKQYjIPcDVmEB6K4CrReSukO7cRfGlIMprykmITfBr/jt+Y++XfsnWJYzOGW07qLs4vhREoHkQ0LLPasnWJQBWQXRxGmbeew2LDqaTOhSCtSBOBSaq6jOq+gxwMmCtCB84Wr6JBRHAZQCmRQiNFoSqsn7Pep9r01q6Fk7Ho0NNXY2JztmaBVGc19BZuX7PesCEOrF0XXxZEP6Wp3XoKAUB0NNrOyOku3Zh/LmYArUIM5MzSYpLahiOVlhZSEl1CYMzBkdWWIvrNLcgWhvxBsaCKKspa6gocgtzSY5LbpgjYema+FrSuKLWTKr052nwDgLZHoINtXE3sEREZmNGMx1D03kRFg/eHUkO/laTcxAR+qf1Z0uJsSA2FpllNpyY9ZauS/NO6tY6HaHpXIieST3ZWLSRQRmDrDuyi+Nr5n1r/VWpCamkxKdQRlm77tnaTOqHRWSCqr4KHAm8A7wNjFNV3wsgd3P89UEEykQwrULHgsgtzAWwFkQ3oPm8mWAtCGh0SW4s2mgbE90AX9F/A0X+dQjFzdSai2k1cJ+I5AJ/Bjar6jRPRFeLD9ISWq4qV1ZTRkpCSsDr+qf3b3zhC40FYUNsdH2ceTPObPvWZt1DY5+VM6hhY+FGhmQMiaygFtdxhs17WxDBND4jpiBU9QFVHQccC+wCnhGRH0XkbyKyX7vv2oWJj40nOS65qYKoLiMlPrCCGJA2gLwS0/G4sWgjyXHJPpeLtHQtmrcKnWidzvK1vshJywGMBVFeU86O8h3WgugGxMbEkpaQ1sSCCKbxGUp036A6qVV1o6req6qjgAuBs4GV7b5rF6d5x6Ov0MzN6Z/en+q6anaW72xwGVifctenuUvSWRDGsUR9kRiXSJ8efcgrzmuwNq07snuQkZTR5sbn02c93e77BTsPIk5EzhCRlzHB+1YB57b7rl2cjKQMiqubZWIrWt7br7yxcKN94bsJLRREEBYEeOZClGyxAxq6Gc0HNQRjQYRCwFFMIjIRYzGcCswHXgMmqWr7usS7CemJ6U38hGU1QbiYPAoitzCXDYUb7KSnbkLzkSnBWBBgysv6Pev5oeAHwFoQ3YXm82bKqstCnusQiNYsiJuAr4ERqnqmqr5ilUPrNHcxlVaXtqogRmaPJDkumalfT2V3xW7GDxwfaTEtnYD2WhBH9D+C5TuWc8OMGzhq0FE2ims3wacF0UrdEgqtdVIfr6pPqeqeiEnQBfFWEKoalIspOT6ZiftM5Jst3wDYZUa7CS06qYO0ILzXnb5h/A22v6qb0Nw7EUzjMxRsbOAI4K0gquuqqdO6oDLx5qNuBuBXh/yKPil2Vmx3wJcFESuxfkMnOIzsO5KR2SMBOHHoiZEV0tJpaL4gWTCNz1AIdia1pQ2kJzQqiLIa45ELJhOPGHAE665aZ/3J3QjHleQ9iiktMS0oi+Cby78hvyQ/4Cx9S9ciI6nRxaSqlNeUR9SCsAoiAjhD0Rz3EhB0Jg7tZddg6k7ExcSREp/SpJO6NfeSQ0pCig3Q183ISMygsraS6rpqautrUdRaENFGemI6dVpHeU15gwXR2jwIS/fF2yVZUlXSage1pfviuCRLqkoaFgKyFkSU4e1XbrAgIqjlLdGN97yZ4qrioC0IS/ejIRhoVVHD+jKRbHxaBREBvBWEMyrFWhAWf3iPTHH6ICwWX3jXLfExZv36SDY+7SimCOCdiYWVhQD0TOrpnkCWTk0LF5O1ICx+8K5bnDITycanVRARwDsTnZahVRAWf3hPfrIWhCUQTeoWT5npldQrYvezLqYI4L3yk2NBOPssluZYC8ISLN5LGjt9EM6+SGAVRATw7khytHwkM9ES3XgvGtSWYa6W7of3ipWOgoikd8IqiAjQvA8iJT6FuBj7V1t8k5GYQUlVCRW1FdTW11oXk8UvvlastAoiynAysbCykKLKItv/YAlIn5Q+KNqw1Ky1ICz+SI5LJi4mjsLKQkSEuJi4VleUCwWrICJAfGw8WclZbCvdRmFVoVUQloBkp2QDsG73OqD1SK6W7ouI0C+1H9vKtpEcl0zPpJ4RDdRoRzFFiJy0HPJL8imqLLL9D5aAOApi7e61gLUgLIFpqFuqIu+dsBZEhHAysaa+pmGReYvFFw0WxB5rQVhaJycth7W71xIXExfx0ZHWgogQjoLIL8lvWGTeYvGFoyBW7jTLvGcmZ7opjqWTk5Nq6pYdZTvI6pEV0XtZCyJC5KTlkFeS17BtsfgjMzmTWIllft58wC4faglMTloOuyt2U1tfy/kHnh/Re1kLIkJ4v+RWQVgCESMx9E/vT2l1KclxyfTu0dttkSydmME9Td1SXFUc8caEKwpCRKaKyI8islRE3hWRnm7IEUmG9x7esG0VhKU1hmeZ8jK452C7fKglIE5ZgUZlESncsiBmAAep6sHAauAml+SIGN6ZaBWEpTX2y9oPsO4lS+t4Nz67pAWhqp+qaq3n5zxggBtyRBKn4xFoWDvYYvGH04g4e/+z3RXE0ulxJuICjO0/NqL36gyd1JcBr7stRLgREWZfOpuB6QOJj413WxxLJ+dPY//EsMxhnHfAeW6LYokCvvzNl/Tp0YfEuMSI3kdUNTIJi8wE+vk4dIuqvu855xZgDHCu+hFERCYBkwAGDRo0euPGjRGR12KxWLoqIrJIVce09bqIWRCqemKg4yLya+B04AR/ysGTzhPAEwBjxoyJjDazWCwWSwtccTGJyMnAZOBYVS13QwaLxWKxBCZiLqaANxVZCyQCuzy75qnq74K4bgdgfUwWi8XSNgarap+2XuSKgrBYLBZL58fOpLZYLBaLT6yCsFgsFotPrIKwWCwWi0+sgrBYLBaLT6yCsFgsFotPrIKwWCwWi0+sgrBYLBaLT6yCsFgsFotPrIKwWCwWi0+sgrBYLBaLT6yCsFgsFotPrIKwWCwWi0+sgrBYLBaLT6yCsFgsFotPrIKwWCwWi0+sgrBYLBaLT6yCsFgsFotPrIKwWCwWi0/i3BagLfTu3VuHDBnithgWi8USVSxatGhne9akjioFMWTIEBYuXOi2GBaLxRJViMjG9lxnXUwWi8Vi8YlVEBaLxWLxiVUQFovFYvGJVRBuUlMDEybAE0/Apk0wfDj8+c8gAj16mG8R6NmzcXvyZKiogDFj4JVXYNUq6NsXzjkH3n8fDjkEfv1rc+4554Cq+b7sMthrL7P/j38035mZcMUVZnvsWKirc/sfsQTinXfg0EOhtBRuuw3OOguOPNLk3x/+YMqBU05EoHdv+NOfGvP3wgvN9qWXQn09nHgiTJoEGRlm/6xZ8PXXsP/+sGULPPYYHHOMKRe//S388pcwYoQ596WX3P43LA7PPmvKQXU1XH01XH65ybOf/AT++9+QkhZVDZOUkWfMmDHaqTupy8rgzjtNRl17Lbz3HixaZCr78nKIiYHUVPNyVlXBsmXmhQQYNMgoiWA4+GBYutRsDxhgXmZ/nHMOvPtucOnm5sLgwcGdawmdjz+GTz815SY21pSJ+HhzrKam6XZyMjz8sPk9YQLMnRvavceMgebvUlKSKau7d8OoUbBkidl/5pkwbVrTc/v0gYKC0GSwBE9lJdxxh8mbmBiIizP74uPhoYfMOUcdBV99ZbZHjzZ1D8Bvf4s8/vgiVR3T5vuqatR8Ro8erZ2WNWtUf/97VdNmVz34YFUR8wHV+PjGY8F8brpJdcgQ1b59Wz/3yitVR41SHTSo6f7kZNUBA1QTE006cXFGjsGDzXdcnGpOTuP5M2e6/S92D2prVVesaJmPWVm+t3v29J3vSUmqMTHm4+y78ELV004zeR5MOevfv7FcDBxoykvzcwYMUE1PV83IUI2NNfsOP9ztf7H7sG6d6vXXt63+aPYBFmo76lzXK/22fDqtgiguNi9r84yJj1d9/HGz/corqpMntzynvLzxhVu/XjUhQfWhh5qmP2mSOaekRHX4cPNCl5WZfSec0PTcF180+5cvD17+3FxzzeOPh/5fWFrHVzkA1e3bVYcONWWptNTsO/lk1e++M9t336363/+a7blzG9Orrzfl56STmt7nm29MA+X99811sbGqmzapTpzYWPZ88eGH5vjLL/s+fsUVqn36hOe/sASmvFw1LS2wAnjySdUpUxrf++OOa8zf2FjVAw6wCsI1qqtVs7ObZtimTeYFXr3anLN+vfmurTWV8fr1prLfvt3sLygwv1VVN29WralpeY+8PLNdVKS6Y4fZ3rrVKApv6utVN2xo2zPU1hrFNHly266ztJ2XX25aVh58ULWqyuS7qmphoerOnWbbO383bDB5W1/fWJ682bPHfJrjfV1urtlXVmbSDoSvezjce6+RvagocBqW0KiqMhaed3kpKFDdssWUl5ISk0/19ap1dY3vfWmp6rZtZnvHDtWionYriKiaKNfp+Phj0+dQUAAnnwy//73pUB440Hwc9t7bfMfGNvXxp6aa7z5eExwHDGh5n/h4yMkx2+npjfv79Wt5rgi0dbZ5bKzpwN66tW3XWYKnshLuu890BAPcdJPJq0mTICGhMd8zMhqv8c5f7zx1ypM3PXv6vq/3dU7Z69HDfALh6x4OgwaZ7y1b4IADAqdjaR+ffWb6FvLyzKCC8883fUR9mk2GduoQ7/c+JcV8wAxUCAGrINrLxo1wxhlQW2t+P/JI4Jeqs9OnD+zY4bYUXZP6ejNo4dFHze8LL4S77nJXplBwGit5eVZBRIK8PDNCrb4eTjgBnnnGdEy7gB3m2h7q6syIAUc5QNtb7Z2N7Gw7KiVSfPhho3IAMwopmunf33zn5bkrR1ekvh6OPdaMbHvpJZg50zXlAFZBtJ1XXzUtqC1b4G9/M2PS8/KMiRfNWAsi/NTWwtFHm2GiYIY1f/mlcStFM94WhCV8fPihUb7r1pn5Tuec47ZE1sXUJlThH/8w/r1bbzWfuLhGf1804ygI1ehXdp0BVTOxzBmXDnDQQe7JE06Sk6FXL8jPd1uSrsVbb5n5UjfeCLff3ineQ6sg2sKcObByJTz3nOk46kpkZ5uO1LKyxo4vS/tZuhTefBOysow78thj3ZYovNhBDeGlogLeeAOOOw7uvtttaRqwCqItPPywCU/xi1+4LUn4yc4239u3WwURDhYsMN/ffAPDhrkrSyTIzrYuyXBy443Gehg/3m1JmmD7IIJlyxYTOuPyy42J3dXYay/zbd0GobNxo4lxlZEB++7rtjSRwYbaCC9ffmmGNV97rduSNMEqiGAoLjZDWuvr4Xe/c1uayOCMTLEKInSc2Dh33tkp/MgRwVoQ4aGszAx2WbYMfvObTtf4tAoiGB56CL77zoxfHzrUbWkigx26GB4qKsy49fPOMxFWuyp9+sCePSaQoKX9PPEE/P3vkJYGp53mtjQtsAqiNerqTNjjE06Al192W5rIkZFhWi9WQYTG66+biJtdWTlA44zenTvdlSOaqa83E2zHjzdlphPOj7EKojU++gg2b+76L7yIsSKsggiNhx82s4u72qil5jiDGqybqf3Mng1r13bqusUqiNaYPdvEQDn9dLcliTzWrxwa8+ebNRZ+//uu2/fgkJVlvnfvdleOaGb2bBMH7eyz3ZbEL64rCBGJFZElIvI/t2Xxyfz5ZvEUZ/GWrkxWln3hQ+H9983EyUsucVuSyJOZab5teWk/8+fDyJGtB050EdcVBHA1sNJtIXxSXGxWZRo71m1JOoasLNi1y20pohfnhfeOuNtVsQoiNMrL4dtvO33d4qqCEJEBwGnAU27K4ZeXXjKjUi680G1JOgarINpPba1xLx1+uNuSdAy9eplvqyDax+uvmwboL3/ptiQBcduC+A8wGaj3d4KITBKRhSKycEdH+sdVTYfj6NGdXsuHjcxM07KprHRbkujjf/+DwkI45RS3JekYUlKM29UqiPbx8MNw4IFwzDFuSxIQ1xSEiJwOFKjqokDnqeoTqjpGVcf0ab5YRiRZswZWrDAzp7t6h6OD0/ForYi28847ZuhndxjMAOadyMw0cyEsbWPTJuO6vuyyTl+3uGlBTADOFJFc4DXgeBF5yUV5mjJ/vvk+6ih35ehI7MiU9rNgAYwbZzqpuwuZmbastAcnTlcU1C2uKQhVvUlVB6jqEOACYJaqXuyWPC1YsMCMLhgxwm1JOg5rQbSP4mJYtar79D84ZGbastIe5s837rlDDnFbklYJq4IQkRQRiQ1nmq6xcqWZ8NSdWoRWQbSPVatMn9XIkW5L0rFkZ5vov5a2sWABHHwwJCa6LUmrhKQgRCRGRH4pIh+KSAHwI7BVRFaIyFQRCSqUparOUdXO5bxdu7brRuL0hzN00SqItrF2rfnubuUlJ8cGd2wr9fVRNXQ+VAtiNrAPcBPQT1UHqmo2cBQwD7hXRDqP2yhYampMR1J3e+GtBdE+HAXRVQM5+qN/fzNyq7zcbUmih9WrjUsyStyRofpPTlTVFuEcVXU38DbwtohE3xTkjRtNkL599nFbko4lOdl8rIJoG2vWmMqyk4Vqjjjea1N3xUWRIoEz+CVKFESoFsR7InKRiPhdgsyXAun0fP+9+T7wQHflcAMbbqNtlJfDBx/A0Ue7LUnHY9cQaTsLFpg5JFEy+CVUBfEEcDqwXkTeEJFzRCQhDHK5izPK4OCD3Zak47EjU9rGrFnGzXLZZW5L0vE4qxBu2+auHNHE99/DoYeaIH1RQEgKQlXfV9ULgSEYl9KvgE0i8qyITAyDfO7wxRcmE6NglEHYseE22sb8+RAT0+nWEu4QMjLMd1GRu3JEE2vXRpU7LizDXFW1XFVfV9VzgJOAQ4GPw5F2h7N8OcybB+ef77Yk7mAVRNtYsMC4IlNS3Jak47EKom2UlcHWrVE1+CUsCkJE+orIn0RkLvAe8AlwWDjS7nC+/tp8n3uuu3K4hVUQbWPFiu43/8EhNdVYT1ZBBMf69eY7iga/hDSKSUSuAC4EhmNcTDeo6tfhEMw11q0z/Q+DBrktiTs4ndSqnT5OjOtUVZnVBqPIZRBWRIwVYRVEcKxbZ76jyIIIdZjrOOBu4DNV9RuRNapYu9aMZ4+STqSwk5lphvgWFze6ECy+2bDBKNIoahGGHasggseZLxNF5SVUF9PfVXWGP+UghgEh3qNjWbcuqjIw7NjJcsEThS3CsJORYUZxWVpn3TrTAHPW0ogCQlUQU0XkbRH5lYgcKCLZIjJIRI4XkX8Ac4HoGPALpjXYHUNseGMVRPBs2mS+hwxxVQxXsRZE8KxdG3WNz5BcTKr6cxE5ALgIuAzYCyjHLCE6HbhTVaNn9ZkdO6C0NOoyMaxYBRE8eXnGFZmd7bYk7pGR0agoLYFZtw6OPNJtKdpEyKFKVXUFcEsYZHGf7hp0zRurIIInLw/69eu+/VUAPXvC0qVuS9H5qa42IXwuushtSdqE20uOdi4cn3J3tiB69zbfO3e6K0c0kJ/fGG6iu2KHRQfHxo0mkmuUNT6tgvBm40bzPXiwu3K4Sa9epkVcUOC2JJ2fvLzGgHXdlexs45atqHBbks5NFI5gAqsgmpKXZ1pESUluS+IeMTHGitixw21JOj95edaCcNaJt+UlMBs2mO8oCwkfrpnUE0QkxbN9sYjcLyLR1wzPz7ctQjAvvbUgAlNeboZ3WgVhvq2CCIwzoKFvX7claRPhsiAeBcpF5BDgOmAd8EKY0u44bIvQ0KePfeFbwwlx3d0bFM4ILtugCEyUDmgIl4KoVVUFzgIeUtWHgbQwpd1xWAVhyM62CqI1HAXR3cuLtSCCI0rrlnApiBIRuQm4GPhQRGKA6FpJrq7OLMDuxLjvztjF6FsnL898R+FLH1asBREcUTriLVwK4nygCrhcVbcBA4CpYUq7Y9i1y8yk7s6TnhxyckwsptJStyXpvDgKoru7mNLSICHBWhCtEaUj3sKlIP6sqver6pcAqroJiK71Op0CbhVEY0G2S0n6Jz/frAGRnu62JO4iYvusWqOszIQj6cYWhK/V404JU9odg2MiOz7V7oxTkJ1WsqUljk/ZhkQ3jSrrYvJPFPdXhboexJXA74GhIuI93z4NiK51IZwWkFUQdjH6YIhSl0FEsBZEYKLYHRlqLKZXgI8wa0Lc6LW/RFV3B7pQRAZihsL2BRR4QlUfCFGe9mNdTI04BdlaEP7Jz++e61D7ok8fWLPGbSk6L93VggBigWLgD80PiEhmK0qiFrhOVReLSBqwSERmeIL/dTyOiewEq+vOpKWZ2eTWbeAb1agdlRIRrIspMFE84i1UBbEI0/oHaO6MVcDvvHJV3Qps9WyXiMhKoD/gjoLYvt2EmIgLOcBt9CNi50IEYvdus9xoFLoMIkJOjumILSw00V0tTXEGNKRF39SwUNeD2DscQojIEGAU8K2PY5OASQCDIrlOdJROZIkYNtyGf6K4RRgRnAB069bB6NHuytIZieIBDWEL1iciZ4rIfZ7P6W24LhV4G7hGVYubH1fVJ1R1jKqO6RPJDmQbh6kptuPRP1Hc6RgRnBDWTsRSS1OieEBDuIL13QNcjXEPrQCuFpG7grguHqMcXlbVd8IhS7uxFkRTrIvJP1Hc6RgRnAilznoqlqZEcX9VuBzupwKHqmo9gIg8DywBbvZ3gYgI8DSwUlXvD5Mc7aOmxrhTojQTI4K1IPzjWBA2LIshJcU0KHJz3Zak8xHlAxrCuR5ET6/tjCDOnwBcAhwvIt95PqeGUZ7gKSgwGWlf+Eb69jWLwNgF6VuydasZ0JCQ4LYknYecHDtvxhe7d5vlRqO0bgmXBXE3sEREZmNGMx1D03kRLVDVr2g58skdnM7YKIvVHlH29ow/WL8eRo1yV5bORkGBLSvN6d/fzpvxRZTXLSFZECLysIhMUNVXgSOBdzB9CuNU9fVwCNgh2DAbLXE6Hq1fuSUFBbasNKd/f2tB+CLK65ZQXUyrgftEJBf4M7BZVad5IrpGDzbMRku8hy5amrJjhy0rzcnJMZVhdbXbknQuorxuCUlBqOoDqjoOOBbYBTwjIj+KyN9EZL+wSNgR2DAbLUlLMytg/fij25J0PqyCaInTCbstutqGESfK65awdFKr6kZVvVdVRwEXAmcDK8ORdodQUADx8ZARTN96N2LUKFi40G0pOhc1NabjMUpf+Ihh43f5xlEQvXu7K0c7Cdc8iDgROUNEXsYE71sFnBuOtDuEHTtMBkbhTMeIMnYsrFhhwihYDLt2mW9rQTTFhoj3TUGBCT8SH10LbDqE2kk9UUSeAbYAVwAfAvuo6gWq+n44BOwQduywLUJfjBoF9fWwfLnbknQeotynHDFsiHjfRHndEqoFcRNm3YcRqnqmqr6iqtHX3LSjUnxjRzK1JMpHpUSMrCwzL8RaEE2J8v6qUIP1HR8uQVxlx47Gcf+WRmwIhZZEeadjxBAx/RAbN7otSedix47GhlYUEs6Z1NFLlJuBESM52bgObBC2RqyLyT/HHQcffgjFLWJudl8KCqK6brEKoqrKFGj7wvtmn32sBeFNQYFpLWdmui1J5+OSS6C0FL6OrtWGI0Z9vRnUEMV1i1UQtkUYmH32sRaENzt2GH97bKzbknQ+Roww37ZBYdizB+rqorpusQrCKojA7Luvmfxkh7oaorzTMaL06wc9etgGhUMXqFusgti61XxHabTFiGNDbjRl61ZbVvwhYl2S3nSBusUqCLt8ZGCGDzffdi6EwS4sFZhDD4Uvv4TycrclcZ8uULdYBZGXZ1o+/fq5LUnn5MADISkJFixwWxL3qa+3S9O2xuWXQ2EhfPCB25K4TxdYmtYqiPx8MwwtSqfCR5z4eDOjev58tyVxn507obY2qluEEWfCBDM8et48tyVxn/x8SE+H1FS3JWk3VkFYl0HrHH44LF5sKsfuTBdwGUScuDg47DDboIAuUbdYBZGXF9UmYIcwdqxZfnTFCrclcRen09G6IwNz+OGwZIltUHSBusUqiCheULzDGDvWfM+e7a4cbuMMW4zS5SM7jMMPNw2K7j6woQvULd1bQVRVmZc+yrV8xBk2DMaMgaeeclsSd+kC49o7BKdB0Z0HNnSRAQ3dW0E4LoMo1/Idwvnnww8/NFaS3ZGCAhOxNC3NbUk6N/vsA716de9+iB07usSAhu6tIJzY9VGeiR3C4Yeb7+7cKnSCOtqFpQIjYizO7lxWukjd0r0VxKZN5jvKM7FDGD3axB+aM8dtSdzDhtkInrFjYdkyMzS4O9JF6pburSAWLTIuA2e2sMU/qalw+ukwdSo895zb0rjD9u1WQQTLBRc0Bqo79thGd253YdEiiIkxE02jmO6tIBYsMKEBEhLcliQ6uP12SEyEv/wFnnkGKivdlqjjyM01L/0RR7gtSXRw0EFw5ZVm+4sv4I033JWno1mwwCiHlBS3JQkJVxWEiJwsIqtEZK2I3NjqBdXVsHu3aY14t0gqKxvHXJeVgWrT61Qbo5HW1Jh06urMC+/41i2tc8gh8NZbprP28svhpptMxZmba/7/1iK+VlSYVjiYc0tKzLXbtpn8KC9vTKO2tlEBNc/f8nIzSsQ5t76+MfbP9u3mPoWFJu26usbzysvNPR23h/d1zeWsrzfbO3fC5s3w6KOmRThpUpv+sm7NI4/ASSeZ7UWLGstKXZ15D6uqgktHtTGftm0z/v2yMpNPdXUtz3fye9cuk9+Vlebc6mqz3yk/W7caeUpLjUto1y5zvK7OnA9Gxpoa//coKjJlrbLSpFVebuRdsKBr1C2q6soHiAXWAUOBBOB74IBA14w2f33j54MPVOvqVAcMUD37bNWtW83+f/5Tm/D3v5v9O3eqjh2rOny46g8/mH3PPaeWNlBb2zQPnM9BB5nvt9/2fV19veqoUeacd99tef2IEY3bW7eqnnOOav/+qjU1qnvtpXreeap5eY3nDBpkvr//XvW228z2O++Y7733Vk1LM9sjR5rvN99svDYmRnXdOtVrrlGNi1MtLW2Us6xMNT5e9eqrVZcuVY2NbbzunHM64h/uepx0UtO8/t3vVE8/XXXwYFMuWuOPfzTXTZ/estxMmtT03FdeMfunTTP52Lu3amqq2TdunGpJicnTAw9smVZCgur69aq/+pVqr16q1dWq++5r5Pfmiy/M+W+8odqjh/mMGdNYjtesMduPPRa2vzBUgIXajnpatHlru4MQkXHAFFX9qef3TR6Fdbe/a8YMHqwLnc6fgQNNy+6ww0wYCDBrFzix6J2x2NA43G7YMFizxmwPGmRaDcuXwwEHhPHJugGrV8OWLY0dcR98AO+8Y7YTEozbziEmxqzYl5hoZteCWTPAaRHeeis8/njT4bPe+ehNa6GkvdMFGD++cXUzkZaWpcOIEY1DV0tKYOVKsz1okLGWHEtm5kw44QT/97f4ZsMG+Pxzs/3WWzBjRmNr3nHxlpeb/POF93DZvn0brVAHZwCFd94lJzdaAd7svz/8+KPZ7t8fLr4Y7r3X5H95ucnzDRvM8REjGtPzrk/WrzeWZfMyNWECzJ1r1rffsMFYTYcd1urf0xGIyCJVHdPm61xUEOcBJ6vq/3l+XwIcoap/bHbeJGASwKBBg0ZvvPJKk8nLl5vKBeDEE00hq683rghn2yE21rzk8fHwySeNmTppUqPrwNJ+Nm+Gq64yL1jz//Ljj8330Uebl++YY+Ddd40Zv//+8O9/w+uvw6uvmn11dSYNEfjoI3Nt//7GvVVfbz6xsebzv/+Z46ecYiqc+Hg491wz0mrwYLjsMrjuOpP3MTEm7X33NXkOcNppphJp3gdVXW0qq9pac86YMcaH/q9/2SGuobJuHVx7rXHb1NSY2E1ffmlcNvvuaz7N2bSpMczLK69ARoZxX+3Z09gAGDMGFi402xMnmvJx3HGmbK5ebRSGo5Sc/L30UjjrLLjmGlMXfPyxKTuxsY3loq7OyNi8nqyvN2UqJ8f0x/XoYZTC5MlGgeXkmIZPXFwE/sS2014F4aaL6TzgKa/flwAPBbpm9OjRjTbTtm3GjfD8822ztbZvN+bfSy+17TpL+7juOtX99zeuqbZyxx3GzVRR4fv4hReqepeJYDn9dNWf/KTt11kiw4wZxr2zYoXv4/X1phxce23LY0cfrXrRRapFRapZWaoPPhhZWX1x5JGmnHdi6BYupjFjdKHTSggFVdsS7Cq0Ny9tGYgunHqqM+ZZZ5bNQ3stCDd9KwuAYSKyt4gkABcA0zrkzp04Iy1tpL15actAdCHSefOsM8sWIq45yFS1VkT+CHyCGdH0jKp28/CPFovF0nlwtQdFVacD092UwWKxWCy+ca0Poj2ISAmwym05IkhvoCsHr+nKz9eVnw3s80U7w1W1zWGIO8cYrOBZ1Z6OlmhBRBba54tOuvKzgX2+aEdE2jW6x04AsFgsFotPrIKwWCwWi0+iTUE84bYAEcY+X/TSlZ8N7PNFO+16vqjqpLZYLBZLxxFtFoTFYrFYOgirICwWi8Xik06tIEQkU0RmiMgaz3cvP+cNEpFPRWSliKwQkSEdLGq7CPb5POemi8gWEXmoI2UMhWCeT0QOFZFvRGS5iCwVkfPdkDVYWlvkSkQSReR1z/Fvo6UsOgTxfNd63rGlIvKZiAx2Q872EuwiZSLyMxFREYmaoa/BPJuI/MKTf8tF5JVWE21PhL+O+gD/BG70bN8I3OvnvDnARM92KtDDbdnD+Xye4w8Ar9BKxNvO9Anm+YD9gGGe7RxgK9DTbdn9PE+ri1wBvwce82xfALzuttxhfr6fOO8XcGVXez7PeWnAF8A8YIzbcocx74YBS4Bent/ZraXbqS0I4Czgec/288DZzU8QkQOAOFWdAaCqparqYx3JTkmrzwcgIqOBvsCnHSNW2Gj1+VR1taqu8WznAwVAn44SsI2MBdaq6npVrQZewzyjN97P/BZwgkjURHJr9flUdbbX+zUPGNDBMoZCMPkH8A/gXiCaFl0P5tmuAB5W1T0AqlrQWqKdXUH0VVVn8eltmEqyOfsBhSLyjogsEZGpIhLbcSKGRKvPJyIxwL+A6ztSsDARTP41ICJjMa2fAMvGuUp/YLPX7y2efT7PUdVaoAjI6hDpQieY5/PmcuCjiEoUXlp9PhE5DBioqh92pGBhIJi82w/YT0Tmisg8ETm5tURdD7UhIjOBfj4O3eL9Q1VVRHyNyY0DjgZGAZuA14FfA0+HV9L2EYbn+z0wXVW3dMaGaBiez0lnL+BF4FJVrfd3nqVzICIXA2OAY92WJVx4GmP3Y+qPrkgcxs10HMby+0JERqpqYaALXEVVT/R3TES2i8heqrrVU4H4Mom2AN+p6nrPNe8BR9JJFEQYnm8ccLSI/B7Tv5IgIqWq6reDrSMJw/MhIunAh8AtqjovQqKGgzxgoNfvAZ59vs7ZIiJxQAawq2PEC5lgng8RORHTADhWVas6SLZw0NrzpQEHAXM8jbF+wDQROVNVw7BSWUQJJu+2AN+qag2wQURWYxTGAn+JdnYX0zTgUs/2pcD7Ps5ZAPQUEcdvfTywogNkCwetPp+qXqSqg1R1CMbN9EJnUQ5B0OrzeRaLehfzXG91oGztIZhFrryf+Txglnp6BKOAVp9PREYBjwNnBuPD7mQEfD5VLVLV3qo6xPO+zcM8Z2dXDhBc2XwPYz0gIr0xLqf1AVN1u/e9lZ75LOAzYA0wE8j07B9D0/WsJwJLgWXAc0CC27KH8/m8zv810TWKqdXnAy4GaoDvvD6Hui17gGc6FViN6Se5xbPv75iKBCAJeBNYC8wHhrotc5ifbyaw3Suvprktczifr9m5c4iSUUxB5p1gXGgrPHXlBa2laUNtWCwWi8Unnd3FZLFYLBaXsArCYrFYLD6xCsJisVgsPrEKwmKxWCw+sQrCYrFYLD6xCsLSbRCRLBH5zvPZJiJ5nu1SEXkkQve8RkR+1Y7rEkTkC89kO4vFFewwV0u3RESmAKWqel8E7xEHLAYOUxOXqa3X/w0TgO3lsAtnsQSBtSAs3R4ROU5E/ufZniIiz4vIlyKyUUTOFZF/isgyEflYROI9540Wkc9FZJGIfOIJJdKc44HFjnIQkTnO+gIi0ltEcj3bB4rIfI81s1REhnmufw+4KLJPb7H4xyoIi6Ul+2Aq9zOBl4DZqjoSqABO8yiJ/wLnqepo4BngTh/pTAAWBXG/3wEPqOqhmFnmWzz7fwAOD+E5LJaQsP5Ni6UlH6lqjYgswyzE8rFn/zJgCDAcE9RthieoWyxmoaPm7AWsDOJ+3wC3iMgA4B1tXB+jTkSqRSRNVUtCeSCLpT1YBWGxtKQKQFXrRaRGGzvq6jHvjADLVXVcK+lUYGIzeePEbI93dqjqKyLyLXAaMF1EfquqszyHE4muhWssXQjrYrJY2s4qoI+IjAMQkXgROdDHeSuBfZvtc1xGx2EsD0RkKLBeVR/ERLw92LM/C9ipJjyzxdLhWAVhsbQRNUs6ngfcKyLfY6Kajvdx6kfAMc32nSgiC4ATgd0ichXwC+AHEfkO47p6wXPuTzDrZFgsrmCHuVosEURE3gUmq+oaEZkDXK9Bri8gIu8AN6rq6kjKaLH4w1oQFktkuRHTWd0mPIu+vGeVg8VNrAVhsVgsFp9YC8JisVgsPrEKwmKxWCw+sQrCYrFYLD6xCsJisVgsPrEKwmKxWCw++X/PrKWXmCYx5AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ch = w.channels[0]\n",
    "plt.subplot(211)\n",
    "plt.plot(ch.times*1e6, ch.volts, color='green')\n",
    "plt.title(\"DS1052E from .wfm file\")\n",
    "plt.ylabel(\"Volts (V)\")\n",
    "plt.xlim(-0.6,0.6)\n",
    "\n",
    "plt.xticks([])\n",
    "\n",
    "ch = w.channels[1]\n",
    "plt.subplot(212)\n",
    "plt.plot(ch.times*1e6, ch.volts, color='red')\n",
    "plt.xlabel(\"Time (µs)\")\n",
    "plt.ylabel(\"Volts (V)\")\n",
    "plt.xlim(-0.6,0.6)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DS1102E-B\n",
    "\n",
    "### First the `.csv` data\n",
    "\n",
    "This file only has one active channel.  Let's look at what the accompanying `.csv` data looks like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAEWCAYAAABv+EDhAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAAA88UlEQVR4nO2deZhcZZXwf6eq904vhHQWEkISskDCTkARxIioIArq6IyooDPOMIrbzIffCDrzjY46bjPO6Mh88+E2o4KKw+IGOqgEAWXpQCCQsITsC6Szd9J71fn+uPdWVzrdnaS765xO3ff3PP10dVX1Pe+te+s971lfUVUCgUAgkD4y3gMIBAKBgA9BAQQCgUBKCQogEAgEUkpQAIFAIJBSggIIBAKBlBIUQCAQCKSUoAACgWEQkVeKyLPDvD5LRFREKozH9bSILBmD4ywRkU2jH1HgaCQogDJHRNaJSKeItIvIbhH5vYi8X0QyRe+ZISK3ich2EdkjIk+JyHuLXr9JRJ4VkXzx8/Frp4jIr+L/PaioREQmisgdIrJfRNaLyDuLXrtMRB6Ix/WiiHxTRBqKXl8qIl0isq/o52dDnOeSeHzJ+zaLyKdH9+mBqt6vqguK5KwTkYtHe9zRoqqLVHWp5xhE5D9F5LOeYwiMjqAA0sGbVLUBOAH4AvBx4FtFr38P2Bi/fixwFfBS0etPANcCjw1y7F7gVuB9Q8i+EegBpgDvAv6viCyKX2sCPgscB5wMTAe+POD/P6SqE4p+3jTMeW5J3gdcALxPRN48zPsDJcTaKgqMAFUNP2X8A6wDLh7w3LlAHjgl/nsfcMZhHOsB4L1DvDY3up0OeK6eaPKfX/Tc94AvDHGMtwIriv5eCvz5YZ7nEmDTgOduBT4xxPv/C7gufjwdUOCD8d8nAjuJFkiF48ZjzwOd8Wf2N8Cs+H/fA2wAtgOfHGaclwGPA3uJlO6nhnnvJODnwO54PPcDmYHXFfhUfK7fBdqBp4HFRcc5K5bZDvwY+BHw2cE+NyJlfBvQBqwFPjLE2K4hUv498Wfxs6JxfRx4EugGKoDrgRdi+SuBtww41l8Aq4peP+tIxhJ+Rv4TLIAUoqqPAJuAV8ZPPQTcKCLvEJGZYyhqPtCnqs8VPfcEsGiI919INHmNGhGZB5xPdG6DcR/R5AfwKmBNLD/5+35VzRf/g6peRTTJv0kjS+NLRS9fACwAXgP8HxE5eQi5+4GrgWYiZfCBYayU64iuUwuRBfUJImUzGJcDP4yP+1Pg6wAiUgXcAfwnMBH4AfCWwQ4QuwV/RnSNpsfn8lci8vqB71XVm4CbgS/pwZbZlfG5NatqH9Hk/0oii+/TwPdFZFos8+1ECuxqoDE+jx1HMpbAyAkKIL1sIZoQAN5OtLr8O2CtiCwXkXPGQMYEopVuMXuAhoFvFJHXEq2i/8+Al74WxwiSn88MI++4+D17geeAh4mslsG4D7ggnmguBL5EpDAgUgD3DSNnMD6tqp2q+gTRpHX6YG9S1aWqukJV86r6JNGE/KohjtkLTANOUNVejeIRQymAB1T1LlXNEVkqifyXE63CvxYf43bgkSGOcQ7Qoqr/oKo9qroG+AbwjuFP/SC+pqobVbUzPucfq+qW+Jx/BDxPZIUC/DmREnlUI1ar6voxHEtgGIICSC/TidwKqOouVb1eVRcRrTSXA3eKiIxSxj6iVV0xjUSmfgEReTlwC/C2AdYCRGZ/c9HP38X/c3dRwPdd8Xu3xO9pJFoJdxK5eg5CVV8gWo2fQbQ6/TmwRUQWMDIF8GLR4w4i5XcQIvIyEblXRNpEZA/wfiJXz2B8GVgN/I+IrBGR649Afk3sgz8O2DxAcWwc4hgn0K9Ed4vIbiKrY8owcgfjgOOLyNXxoiI55in0n/PxRBZCqcYSGIagAFJIvLqfziCrY1XdDvwT0cQxceDrR8hzQEXsjkk4nSI3j4icSeSy+DNV/c3hHlhVL9X+wPDNg7y+h0ipDBc0vg94G1Clqpvjv98DHEOkBAcVfbhjHIJbiM73eFVtAv4DGFTRqmq7ql6nqnOIXCP/S0Rec4TytgLTByjz44d470Zg7QCF26Cqbxji/UN9FoXnReQEopX7h4BjVbUZeIr+c95IFHMZ7VgCIyAogBQhIo0i8kYiX/H3VXVF/PwX43TOijgN8wPAalXdEb9eJSI1RF/aShGpSdJIJaIGqIr/rhGRagBV3Q/cDvyDiNSLyPnAFUQuCkTkFOCXwIdVddD0zlGc6wQid8FwMYX7iCam38V/L43/fiB2pQzGS8CcUQytAdipql0ici7wzqHeKCJvFJG58eS9B8gRBaGPhD/E//eh+PpeQb/7ZSCPAO0i8nERqRWRbHxfDOUOPJzPop5IIbTF5/SnRBZAwjeBj4nI2fG9NDdWGkc6lsAICAogHfxMRNqJVlWfBL4C/GnR63VEgcLdRMHQE4hWnAn/Q+ROeQVwU/w4CZieEP+dTLSdQHHh1LVALbCNyN/9AVVN3nsdUYDzW0XunIET9tcH1AEsG+Y8j0veB6wnsmDeNcz77yOakBMF8ED8WfxuyP+AzwN/G7slPjbM+4biWiKF2E4U77h1mPfOA35N5Er7A/DvqnrvkQhT1R6i7Kr3EV3fdxO5u7oHeW8OeCORW2wtUUbTN4mCt4PxLWBh/FncOYT8lcA/x+N/CTgVeLDo9R8DnyOyjNqBO4GJIxhLYATI0DGlQCBQjojIw8B/qOp3vMcS8CVYAIFAmSMirxKRqbEL6D3AaUSut0DKCZV6gUD5s4DI1VRP5OJ7m6pu9R1SYDwQXECBQCCQUoILKBAIBFLKUeUCmjRpks6aNct7GIFAIHBUsWzZsu2q2jLw+aNKAcyaNYvW1lbvYQQCgcBRhYisH+z54AIKBAKBlBIUQCAQCKSUoAACgUAgpQQFEAgEAiklKIBAIBBIKUEBBAKBQEoJCiAQCARSSlAA45D7n2/jhbZ93sMIBEbNXSu2sq29y3sY45YHV29n9Ta/73pQAOOMfF659vuP8fXfrvYeSiAwKrbv6+bamx/jloc3eA9lXKKqvOubD3PpV4fbfqK0BAUwzti0q5P27r6wagoc9azcsheAbe0H7T0TADbv7gSgN+fXkPOoagUxUv596Wrue7aNqU01PLV5D129eVSVC+e3kMkID6/ZwacvP4UL5g21N7cNK7fs5c03RpslPbJ2J6//l9+RzQj7e/p48xnT+f0L23lpbzcV2Wg71ctOncaj63ayeXcnldmDdflFCyazbsd+JjfW0NWT4+pXzOKM45stT+kgVJVP3LGCGcfUsaZtPxOqs0xurOGny7fQ3ZejoaaS15w8mXtWvsT+7j5qqyp47cmTWfpcG929eS5eOJmH1+xkV0cPPbl84bxft3AqT2/Zw8LjGrnh0pNdzzHhnpUv8e9LV3PhvBbue66N3R09VFVkuOKM6dzx+GaKO/Hm8kpDTSV7u3p5+9kz+NXTL9He1UtNZZaLTppM67pdvLi3iyvOOI5H1+3kwvktXLtkruPZRfz3sk384JENvHLeJO54fDNNtZVs29vN1KYaWhqqAbjz8c08vXkPbe3dVFVkaK6ror2rF4C3njWDnz2xhc7eHBOqK9jX3Uc2IwhwzYVz+JNzZrqd27cfWMt3fr+WmoosddUVXDhvEvesfImu3ug+veikyTywejuvOPFY7nuujb2dvWQzB27vfPnp01n63DaWzJ/Mz57cQl8uT1NtJRedNIUbl0ZW/pxJ9R6nBxxl7aAXL16sI+kF9K+/fo5//fXzw76nMis8/znf/aYv/er9rNq6t2THn9ZUwx9uONI9xceWrXs6Oe/zvy2pjHVfuKykxz9c/uK7rdyz8qWSHLuxpoInP/X6khz7SLjsa/fz9JbS3bOe13LW9b8wkXPJoqn8x1Vnl1SGiCxT1cUDn0+FC2jhtMZDvmdKY43BSAYnn1e6enPs6+4tqZzO3qH2Obchn1eWrd9Vcjm9uSPdN33syOWVjp4+2tq7eebF0k2MxzXXluzYh0JVyeWVbe1drNu+f9D3NNVWDvt3oJ+aSr9pOBUuoEXTD72P9AnH1hmM5GBUlTmfuMtEVs7R19jVm+Okv7PZhXDHvh6mNtkr9G17uzj3H39jIitxA3rwzm88zB/W7Bj2PZedNo1bHt5ATWWGrt48bz1rOt95cJ3NAMcAy0WEpw8mFQpgenMtN111Nj25PDUVWY6pr6Qvp2xr70aBj/zgcaorsi5j27Srs/D4rWdO5/WnTGX+lAYeXbuTprpKTprawKqt7bR39XLmzGbWbe9AiRRHe1cfJ01r4KW9XeTz0Y1UPC3s7+ljw44O/vme5wDozfutjJ9/qT/V7ZJFU1myoIXaqiyq0N2Xo7muiqwIc1rqaV23i6a6SrIizG6p57H1u2ioqWTu5Ak8sXE39dVZ5k6ewIadHYXz3t/dx/Pb2rnx3hfY1t7logCe3LSn8PgvL5zDrEn1/OjRjSzfuJvPv/VUbrh9BQDvOe8EXjF3Elk5cBKfP6WBlVv3srerl8aaSioywqxJ9SzfuJvTZjSxfkcHezt7+ef/eRZPz20y+Z86vYmrXn4CZ85s5vENu2msrWThtEZ2dvRwXFMNp01v4pzZE3l07U5et2gql506jd0dvVx7y2P09OX5s/Nns2DqhMK1nzdlQuE++X+/e4FH1+2isydHbZX9d3PHvh4ALj55Mje84WSef2kf+7r7OHNmM2vb9pNTZU9HL2ed0Myy9bs4Z9ZE1rQdaA3lVNm1v4fFsybSum4nx9RH53ni5Ak8snYHzXVVfOQHj5ufWzGpUAAAr1s0dcjXbn5oPfu7+wxH00+xz//Kl83knFkTAZhdFBg64dj+x3MnNxx0jEXHDW3hvNC2r6AAPCeN//z9usLjj71+/qDnkTCnZcIBf59Y9PfcycWPDzzG8o27ufHeF2hzyjp59qX2wuMPLDmR5roqWtftYvnG3Zx/4iREomvwoYvmFQKkA5k5iCWanPP8KdH53v3UVrbu8ckS29PZ76acPamePz7neADmTem/Fsk5vOPcKICbXL+J9dG9Pam+ii17unjny2YecD2h/17f1dHDo+t20dbePehnUmoeXL0dgD85ZyYntkw44B48ccD9mdyHA+/bA99z4GvJ93taU43r9zIVMYBDUV9dQUePj398TZEP9aSpQ0+KI2VaUw2NNRUc11TjZmru3N/DbY9tKvw969jSZD1MrKsqyPOguHivOR7LydMamHFMLTOOqeWaC+cAMLG+atSyvCaNYp//5acfN6JjXHXeLACmNA6uBAGOiT+/XR0+1/Ib968BYE5LaTN0RMTVBRQUAFBXlWV/j48FsK+rDxF49rOX0FAz9oGyuqoKWv/2tVx+xnQ3Z2OSD/7/rjqb5z57KRWDpKyOBYlfPJf3OdG9nb2cNLWB5z93aeG5910wm3s/toRMRrj+kpN4/nOXHpQqeOT4TRr7Ykv5e+87l4sXThnRMd7/qjk8/7lLh73fs/G1zDtpuo6eHEsWtBy02h9r/CI5EUEBAPVVFXR021sAq7ft4+v3rqa+qqKkMYiqikzkfnCaNlZujXzj58yaSFVF6W65ZGLNOU0aezv7aK6rPKAmQ0QKfxc/Hg2RK8n+HLt6c3zijiiOkazQR8LhfA7JxOihy3+yfDMbdnYwc6KN68kzFT8oAKCu2scCeO93HgGiIGipEfzcBpt2ddJUWzkmro/hyMRB1byXBRAHb0uN16rxjsc3s35HBxBZzaUkUwiQ21/Lj/5wOYDJtUR8s4CCAiC2AHpy5po4ucctXBbieKPt7ew1yQMvWACOLqBGg/MUJw1QUeS6qq8ubf5Ico5OlxKAxtrS58gIuGoAdwUgIlkReVxEfu41htqqLLm80t1nmybZUB1NFhY3uSBupuberj6TL1OSVulR7vCVe55jy54us4Inj0tZPOlbWQCeGTIm1pyXNo9xVwDAR4FVngOodAoeWkyKCd4WgMWXKVu4jvb1Dl/7TdRqpLqEMY4EQVziOcX5+HVVJbYA4t9eQWCAmkqb+gOv2Bw4KwARmQFcBnzTcxwJ1pehFFk/Q+EZA7DyjRcsAL96N17aW/oahKSewJPRZzINj4wDC6DH4Eby/F6CvwXwr8DfAEN+0iJyjYi0ikhrW1tbSQYhJDeb7ZVoqDGsw3M0Nfd22riAMvHd7LFqTGo4Tpl+6L5To8XLmrNsJZLcrp4ZMhZdOr2VuZsCEJE3AttUddlw71PVm1R1saoubmlpKdFYYlklOfrQmGQZxBRyKhzuNnsLwP4c501poKoiw3viIqdSIk55QJbptYUYgJnEfuZOnsDpM5pYHFfllxKva5ngaQGcD1wuIuuAHwIXicj3HcdjjqUF0L+iMhMJRE21OnpyJtkxnllAqsqM5loyJXaNFMuzxvJz7c8CcrqWx9i1n0hlDEBVb1DVGao6C3gH8FtVfbfXeKIx2cpLVjmfetPCkssquLlKLulAkhbUpc4agchvnBEnBQB2CfpOLqC++HOdN7m01bEAGacFC9hey9S6gMYT4uQDSsS99/zZdjKN7zaNozsZoxhENiNulcCG87+LBkiyq266+qB9RUqAYysItbtfvRkX3UBVdSmw1Et+f83h0bM72pHiFedIvsBGnhEyIj6VwIYivXLHk6SYCoOLmXG6XyG6Zy0/4VAJ7IyXf9xSoNd6pqAAjDRANiNOLiA1nZhdsoBiC6DUKaBQnAbq486zupQiElxA3nhNjrY3WizT+GZL5mKryTErPi4gVVsXkMfEmMQALBSAawzA+Fp62gBBARThYQCY3WiFtDrjGICxCyibdbIA1FaZu7hGDBWAFGIAJRd1EJbWnHeoISgAfM1Na3+ulwVgFgQWHwUAdjndXtWjiQVgEQPwLASzXJgl8rwICgC/AKnlatxrpWEeBM6IT+646bX0CgLbxXM8u4GqYpsGaiNqUIICwDEGYOpr9OmtkkzGpjGAMncBgU/GWs7SAijKzfPAzppLbyXwuMN6cnQJApvHAKLfpnUADs3gLD9VbxeQSRC40Nep5KIOQlXNLNZEnhdBAUBhdvRYVVn6jcHPAjALAmfEpR10ZAFYaXMfBZBYAFmD8/SyWCFSOuUe0E8ICoAiN4y1BWBaPBTLtBMJOASBM+KyIQzYFQ+5NYNzSAP1iueUe0A/ISgA/AKkil0QwKvldX8MwEZeRvz2BLZ251mTyyvZjJhYOl4LFjCO54QdwcYPHjeb9X1mX+uQuIDKvBLY3Hr0KQSzcP9AeiqBE3leBAWAo7/RK8XNEGsXUMarEhhDCwC/VhAW7h/wi1n1y7R0AYUgsCtuGTJYug18TADrIHCFWyWwod/YLQhskwIKxRvCuDiByt6dlxAUAJ51ALbBJrD/QiUJOWVfB4ClBeCzKXwunyebtW2R4JDQZV4J7ElQAEV4rKrKvxlcOiqBwT6eY41lDMBzS0hzd17IAvLFL0BqJ8urrtK8EMyxEric5UGkzK1iAMUyrYkKweyC3ancEnI84ZUiadhyxC2ron8/ABt5Gbf9ADBbNnoVD/Xl1C4G4LgjTN68HbQfQQGA21WwrB713hHM6jwr3NJALXeR8tlEJJdXs419EileFoDp5j7BBTQ+cIkBGMsp9zRQ1z2ByzxzJKeGFoBzDMCKsCn8OMAtC8h2I1l7mdhvCOO2JzDW95FTIZiVBeDYCgLLXkChG6g//f5xW7mmfccLQm3kJaTFArAO6Lu4gHL2CsBp/jedmEMQ2BmvHPli2SWX4x4DsJHn1w7adhtBl0pgVbJG0XyvxIxEpl0voOACcse7Gs8C7w1hbNNAndpBG8kSxGVizOUtYwDRb7c6ACNZXm09EoICKMKjoZd9FpB1DCD6nYZmcOUeBO6zzAKKT9IjnpOGa5kQFACeewLbVhxCWiqBbWQVY9lDPpJnTz6vGHWCcLYA7ArBYoFuuCkAEakRkUdE5AkReVpEPu02Fkd/Y/nHABL5Vi4gXCwAwDSg7xMcNbRY4w/T41LmTZMzfCuBK9wkQzdwkaruE5FK4AERuVtVH7IeiNuGMKaZI86VwGZB4EzZt4IQ8YkBmDZJK2QBOaWBGnZ29cRNAWh0ZffFf1bGP57xEAcXkGHFoVNanfWGMBlx3ETEWJ41lr7xjNP9Csn30lBeGl1AACKSFZHlwDbgHlV9eJD3XCMirSLS2tbWVtLxeNQBlHvPkSQhx9Kn6vJ9SkHg0HSvXMf9AEy/l04pvQmuCkBVc6p6BjADOFdEThnkPTep6mJVXdzS0lKScfSvwh1iAGaThm8aqOXk6LZqtFSzXrOGsQXgE9A33tsh7TuCqepu4F7gEg/5fq0g7PAqdrOuBPYMqtluCGOPT8zKTmaC9e5unnhmAbWISHP8uBZ4LfCM13jAq6d7eZfWF2IARneamwVg3Nap3OMcXnUrkUzbidnTBeSZBTQN+C8RyRIpoltV9eceA/FKkSyWbSXHKw3UboONdOwi5YKCGCpy8FPmaWkH7ZkF9CRwppf8YvzMTTuBaUkD9eqVb+k2AL8CKTFyGhTaQVtv0pTErIzkWSqawRgXMQBvPOsAyr8QLAkCW7q6yttt4OnmsrZyrIPAyeeaFhdQUABFePTJsVY+XnvX2gWBfU1qC7z2kbVUcv0WgI28hEScWRAYXG/YoADw65MTybbNq7Zeb1i7gNxiAKYZMn5zhnV2jPWGMAUXUJnfrwlBAeCYIWMaA4hlmtcBRL9N00C9MmTKPAps+bn2F4LZ0m8B2OCcBRoUQITPZfBoO+sXA7CR57aiMt0UvvwzncAn3dUlBpDWVhDjDfMYALabiED59wLy65RpWwjmoQGsP9eM2Gd0JXOAXdKCbzfQoADwzTku9w1h7OsAyr9TZmTllLmbi+jztI8BmIoLLqDxgFsrCOPAobVM8KgDcGyTU+ZWjrWbKyM+LS8S2VYEF5AzXo3STIPATlaO9YYwIvi4RxyupTXWMQDE3gJIS/PChKAA8DXD7L5QPu111dgC8GyUVvZBYONzzDgo80IQ2Eyin5UDQQEcgLlf1biBGDhYAHnjILBnVXcKWgjbxgDEPgaQyDbOzvMiKAA86wDKv4GYdRAY/DplWnZ29eoFZEnGwT3S3wuovO/XhKAA8MuRt+077hPnKPhUrbpI4hkENpJjI+YgrF1AImLfC6gg20ZeyAIaB5ju5DRQtvGN5tHvCIzbQTt1A7WVZyquINO0EAy/+9WKEAQeR5h/iQ1l+WUBWfcCctwRzEyQU+V6JNxMnsvkaJy15k1QAFC4p+1dQPYmoH0riOh32VcCmwaBE5n2GV22rSDsg93J4sE2ay3EAFzxKpKyrKz0WtBY51U7dUkw3RTetXLdUFZG7PcDKNStGMkLLqBxgKe5Z98LyKsOwK4bqFefHNNeQE6YWwBOdSvlvjBLCArgAHxuNhPcuoFGv233BPYsrbHDw2VpiYcFYJ0FVCzTg6AA8HUBWS3m0tILKBXdQAsuIHv/uK314dAN1NoF5FjUB0EBAH51AGDpa+xPBLXEoxeQT5sEwxhAItNEWj/WaaDRosEnCGwZ0Q8WgDNuPtUUdANVVdNOoJ47gplZcymoXCeWlc/byQP600CNxXoRFEARHt1A7fcDsCWvatoGwm9HMA9rzhZLKweSdtBl3guoWKgDQQHg6FO1nDScdgTLq20fIK8YANhPzC6To3ElsHkQuGAB2LVoOWpcQCJSLyLZUg3GCy+fKpR/4DBvXDzkWyVrLNOhSta6F5DXHh2WSQueDKsARCQjIu8UkV+IyDbgGWCriKwUkS+LyNyRChaR40Xk3vhYT4vIR0d6rFHj2ELYCs/AobUFEMl1qJI1kuWdO26Fx6bw/UkLdjLHcxbQvcCJwA3AVFU9XlUnAxcADwFfFJF3j1B2H3Cdqi4EXg58UEQWjvBYY4JLDMA4D9RjPwDTIHAKAqRe7jzLynXw2RLSuh20W8wqpuIQr1+sqr0Dn1TVncBtwG0iUjkSwaq6FdgaP24XkVXAdGDlSI43GgpfKIfOg+aThkMaqK0F4BUg9TfnS42llQNxFpBXl9Uyr1tJOJQFcKeIvEtEJgz1hsEUxJEiIrOAM4GHB3ntGhFpFZHWtra20YoaQn78oIwLSL3OMe80M/rEc6wzuuyDwLZ1APYxgIRyz+hKOJQCuAl4I7BGRG4VkbeISNVYDiBWLrcBf6Wqewe+rqo3qepiVV3c0tIylqL7x5DIKsnRh8a0HbSDzATrNFDwqZK1wq+mwzgIjJ8FYDkxj9tuoKr6E1W9EphFNElfDWwQke+IyGtHKzx2H90G3Kyqt4/2eKMYh4vcyAVkl26WyLTEOgvItUrWSJbbDnaGdSvg4x9PJmO79Ozx7QICQFU7VPVHqvoW4HXAGcAvRyNYojvpW8AqVf3KaI41VpRze103t4F56mC/XEtUMfQbpyPO4bIfgHUW0NHQDVREpojIh0XkQeBO4FfAWaOUfT5wFXCRiCyPf94wymOOCK/J0XJ949fwznrV6BPsBvuJ2SV90LgXkEuDRqzTQO1kDWTYLCAR+QvgSmABkavmf6vq78dCsKo+gLv+i3D1qVoXgtmIK+CVHePR8ygN19ISQcxjAP3da60a+/lOgYdKAz0P+DzwG1W1bstkhlcg3jarIokBlHfmiGdShbVoHwPAOAbg1ArCCo9it2IOpQD+QVXXDfVi7MefrqqbxnRUTvi0gy7vZnBq3EDGs0jKCnG6mB57Alv3Ako+VLPkDBMpQ3MoBfBlEckAPwGWAW1ADTAXeDXwGuDvgaNcATitjg3lFW40hy+USyVwWRf1+WAY54aCLKcgsKVMQ1kDGVYBqOrb4/YM7wL+DJgGdACrgLuAz6lqV8lHWWL80uosYwBOlcB5YxdQ/Lus23oUyTSVZ6jkADKZ8t8S0ntT+ENZAKjqSuCTBmNxw21FZdoOul+mJdYTo2uw2zoIXO7X0mFzH/N20M5OoLAfQDFl3A/aMz/e1gLwceeBvQuojG9XwGtT+CQGYC/Tg6AA8HOP2LaC8PCoOviNHd15VvRXdTs1SrPCpRtoLNpInrcLKCgAPOsA7HvIu+x65pCb6ZM+aGvNWWPfDM5PyVk29vMMAh9uJfD5IlIfP363iHxFRE4o7dDscM0dN5bt1VvFCq8USTDe+Yw0pPT69K4C+/ocLw7XAvi/QIeInA5cB7wAfLdko3LC0xQrNV4xADTK5rCi3z9evj2PvCxWayXnsSl8gmka6FHgAurTyBa7Avi6qt4INJRuWLa4+cdNJw2f0GFefbKAPLBrIOYUs3Jo7Jc37j/g4QLydAIdMg00pl1EbgDeDVwYF4eNaCew8YhnD3nzTUQc8qo9JuWyrgQ2lFWMfVsPewvAox20J4drAfwJ0A28T1VfBGYAXy7ZqFKEeRDYSF6CxyYi4HGe9oVgLq0gjGMA5mmg1u2g8XUBHa4F8Neq+vHkD1XdICKLSjQmN8q5u2JaNhJ3S5Gk/Du7WpMRIWesAVwqgW1EDcrhWgCD7f516VgOxJM0FEn59cix30gcytvS8VXmdvJ8NoVPXEB2lcDjthuoiHwAuBaYIyJPFr3UAIzJvgDjAa8AqWVpvV8rCEx9QK41HeW+KbyxOy/jUQiWPDBemHlxKBfQLcDdRHsCXF/0fLuq7izZqIxxS5EE8xvNo7uu5abwXhkylvj1rrLfE9hrU3jLe3bcdgMFssBe4IMDXxCRieWiBNwqK02vvI9vPG/tAkoelHEWUEFmmZ9jtCewrcx+F5ANHsVuxRxKASyjKC4y4DUF5oz5iBwp5z45nkrOY0cwD0un7IPA5o39fIL5YN+m3YtD7Qcw22ognngF1cChg2QKWgiDU4DUuIWwS6aT4bXMOGTIWLeDjmSO0yBwMSJyOXBh/OdSVf15aYZkj1dQzdIEcOt46mYBOGQ7GVcPlfOCJZJlvyl8wQVkWQdgJ+ogDrcZ3BeAjwIr45+Pisg/lnJglvhVVqYkC8gQvz455V89ar1SjbqBmooc0t9dKkRw1QCHawG8AThDVfMAIvJfwOPAJ0o1MA9SUQfgco72vYDc0gfLGMuYVYT9pvBqrAGOph3BmoseN43xOFzxrKy0iwH4NLzDelN4L/+4qTJ3inM4uPM8+nOBcQzATNLBHK4F8HngcRG5l0g3XsiBdQFHOX5BNSu8Gt7ljScNL/+4aWO/IpmWWJ4j+LiAko/UatHioeSKOVQl8I3ALar6AxFZCpwTv/TxuCncqBCRbwNvBLap6imjPd7Ix+Ej16OBWLk3SfPzj6ckpddQnmDfDTRxOVkrcy8O5QJ6DvgnEVkH/DWwUVV/OhaTf8x/ApeM0bGOOjwaiLkkOhlnjkB5V3UnlHtbj0wmLZvC+zGsAlDVr6rqecCrgB3At0XkGRH5exGZP1rhqvo7wL2a2DNzxArXNFBDeX4ZXXa4xqyMazrc9gQ2kndUbAqvqutV9YuqeiZwJfBmYFUpB5YgIteISKuItLa1tZVKBuAzOVrh2wzOflr2qOko90Iw64/UY3L0qAT27Ft1uHUAFSLyJhG5mag53LPAW0s6shhVvUlVF6vq4paWlpLI8Fw12neQtMWtHbRLENhGll+qq+2ewOLRDdQ4D9Q7BnCoIPBriVb8bwAeAX4IXKOq+w3GZk55Fw/5+cZN00DdFJ3/l7nU2LeDLv9eQDC+m8HdQNQS+jpV3WUwHhfc2kGXc9AhJm/dQtizT04KgsDWzeCsg8CJBjA7TYd+R8UcqhncRaUULiI/AJYAk0RkE/D3qvqtUsocdBxORVIeWUBlHwROQYBUnFK6rFN6M56bwpulgY7jbqClRlWv9JSfkIa8arcgsHUhWJFcW3l2Aj0D+tZFffm8oTz6P1NLt6WnCXAkrSDKHo+KPDP3iGfg0DJ10Gt1jIc1Z4vHlpDWFArBzKw5h4y1IoICKMJjcrSicEN75FUb+40Lcg3x2BTeBdN4juOm8IbrsnFfB1DuuFXJOrQPcIlzGMrzjAFY+7rKPYcg47ElpK04903hgwLAuUrW1gPk0lzL0pR33d3NSo5DQN96r1zAdVP40AoiRfgqYdvMEZdN4V3qAOwnRys8lLnHxOhRCJZMx1aLFo92F8UEBVBEOZubTl4ul9xxKO/J0SWrKpFtGtD3WLBEv80UgHMdQFAAOLdJsM4ccUiPtJ40IrlmIl0mR7BWcvZdMj32A0hcTqZpoI4EBUBK/MYpKHaLsI/n2E+ODud4gGQbBPtN4T32AwhZQM54R+JNKKyMy7fjKXhbADa4tS7BwQKwEwf0fz/MLADnyScogCLKOgvIq9oZw2I3fAP61hldlvgoGyFv3Ayo3wWUjm6gQQHgWVpv5x/3SwM13hTeY+8BcyvH4RyNe+REsuwtgKT1hHUVslcmUFAA4NYmASwtAJ9ah7xTm2RbF5D95Ag+mU6WRCmStjLzxvEcT3ceBAUA+JXWp2NHMOt20P1yrTC3ABK5DksW65oOr5hVxshs9UrOSAgKoJgy7iGflgZiaQiQugS6jZukQRSItd4PIKSBphDf7RJt7rTEp+lRWu9TCWyPZQdJsD3HfjeXnUyP/XI9CsEgxABccQuQFgsvtRivQrBIupk8jx3B7F1AfstT+15AhgIpigEYyfOq0E8ICgCfrAqwvejZ+Bxzxt8oy2pnwCWg77E6hvJWchArOqf2LGaFYKEb6PjB3Awz9I9nMz4KAIw3hY9/+/jHjXBRcrFo80Iw+wVLIttWrq28hKAA8DXD7FYa4tJeN2/eC8j+alpPjj5KLnGN2NYBmLuA8saFYE7p2QlBAeDtH7cjK/a9VcyDwEVyrSnnTeF9LAD7VsnWQeCEYAE44lcHoOZ7rOasN9mm/LOAPPu5W+HVKNEtCGw0M4YYwDii3DtlZjI+e6yaug0cOrumwQWUnKRtKwi/jC6PDek9CAoA3DplFok2IStinwUEpifpkVft1vHUUKaaJ/T6uGatC8E8W9FDUACAY6dM44ueydgrAMtMJ3AK6Buvjl33rzCOAYDttfQqBPMiKADS0ycnm3EIAmNsTnu0STBeHbtsCekUAwBbt6V1M7iEVGYBicglIvKsiKwWkesdx+Ei17pPjkcWkPmm8A67ZRVkl3MhWPzbNGkh4xDPcdoPIHUuIBHJAjcClwILgStFZKHXeMBJCxv3VjHPAnJqBmd5Kf26gdrRv+2l/WLJ1gKIfpv3AjKRdjCeFsC5wGpVXaOqPcAPgSs8BuLmAjKWl81gvsOSVztoS8xXxy5urli0QwzAEq8gsBeeCmA6sLHo703xcwcgIteISKuItLa1tZVkIGnoIAlxFpBHIZipxFiupSzj1bGHm8u83QX930sPC8B+c58UxgAOB1W9SVUXq+rilpaWkshw7a5oWgdgv8eqKuZuroJcI8zrADyCwP2pTmYyMw6WDtYxqxS7gDYDxxf9PSN+zg17F5CtwGzG3gIA+/4x4BQEthZY3iGrwn1jbQGkpQgMfBXAo8A8EZktIlXAO4CfegzEa9IwXhzHWUCGAomUXFq6gVrhWetgicfqOG98vyZ4ZQFV+IgFVe0TkQ8BvwKywLdV9Wmv8URjspdnbW5au4DyDucIPlWyVieaBjdXJCs+T8PMteh+dehemzYFAKCqdwF3eY4BfKvxTIPADpXAim0voGR9bOpeMw6QelisHnsC91s6lufpZLGmsRAs7Vhf9IxXFlDZWwAHyi41PllV9hWyyURsuWaJXED2MSsvggKguLdKeU+OWY8sIHz2A/AJkFqnDtrLsk0Dtf9eegWBU1cJPJ7w3BDGWgF4WACW04bHDkvp6AZ6oGwLvCwAlw2M7EQeQFAA+JjUHtLFIQsInL5QHs3gjEuBfdqX2/vzrJW5rQsovZXA4w7rr5N5KwiHLKDoC2Unz8Oas3aP+HQDtVc2HoVgfmmgIQjshkdaXYTt6tgjC8h8U/hCmwQ7PNwjxXJNZDm0A/XY98ArCBxcQI54pmKZttf1yALCKQvIdEew2AVktSl8QbCJuMFlG1CwAAxP1LxuJf4dgsCOpGVHMJcsoBQ0gytg1gvIsRmcw+rY8pZV40Iw7zzQoACKSEMWkMum8B4mdRpaQXgEuu1EOm0K7xQDCIVgfvSvqGxRa/+4CDkHJWeJOCbWlXcQ2F62h6IzjwEkD4ILaBzgkVZnaQE4ZAHhVAlsibV7JJmgeg21uU8dgEcQ2DoN1EzUoAQFECPiYAEYy/PpBVT+lZXW7pGayuhr22O9vyc+rb2tN4X32W/Bh6AAYlwClcYB0ozXpvCG8lx3dzM60eqKLADdvTkbgXjVATik9FpbAA6prsUEBVCEx4YwlgFSFwvAPK3OoVWy8X1TXRF9bbv77CwAn3bQ0W9rC8ClcDEEgX0REbeLYIWHBWC+KbxHq+QBsktNwQKwVAAeNQdpiAGYSRqcoABiBJ80UEsyGY8dway3EeyXa4V1IVh1ZWIB2LmAkrvVVJknktMQAwguIF9covHW7aAFlyCwQ/8wU+XaF3+mlVmbr1NVLKe7194CsI5ZgXUMILSCSC0ugUPDr1TGIQaAWvfJty8e6oldMZVZozTQjFCVzYQYQAnI532CwF4EBRAjSNm7gLJOMQCPoJolvXE6ZmWF3depuiJj7AKKMF2wOHUDTUu3VQgKoB+xj8Sr8c3m0w20/KtHk4KsKiMXEERxgHIPAidX0zYLyLoXUPQrxACc8WpYZt1bxT4IbN/uAmyVecECsFQAFVnbGIDjnsC2k6PPpvBeBAVQjEuqm52sbMZ2NQUO7aATuYan2ZOzjQGAvQvId09gO5n2rSBCDGBc4NIKwrodtDgVghnK8+gG2ttnbwFUVfi4gHz2yy3fQrCE4AJyJgoCl3eRVMZhPwDAdNbw2BGsEAOwDAJXZo2zgAp5QGYyM/HHabspvO2qPFkz9Obt+zpBUAAFvIo/LMVmjXcE6y+QssNjRzCfGEDGuBdQ9NunrUf57gcwc2I9AGva9tsJLcJFAYjI20XkaRHJi8hijzEMpC+nPLRmp73gMs4CSr63Ht1An32x3UyWXwzAoxuooaxCHYCdTOv9AE6a2oAIrNyy10xmMV4WwFPAW4HfOck/iJ5cnhWb97Cns9dMprUzpiIr9OXVbEWVBJw9ioe++cBaM5mJBWCZBlpTmaXL0ALwILGoeg3bXlsXgtVXVzDjmFrWbN9nJrMYFwWgqqtU9VkP2UPxmSsWAbCnw04BWFfJNtRUkssrnUYTh73X2CerwiMI3FhTSXtXn5k8jz2BJ02oBmDHvh4zmR6FYI01lezvtruWxYz7GICIXCMirSLS2tbWVjI5U5tqAdjbZagAsF0dN9ZUArC30+Zm8/Ab9xS5RawC3kkQ2LISuLG2gr2m1qp9PKelIVIAbe1dZjKt9wMAqK+qYH+3jzVXsjtWRH4tIk8N8nPFkRxHVW9S1cWqurilpaVUw6WxpgLA5UtlRWNtfI5GSq6/eMjuCzW9ubbw2MrS8YgBNNZU0t7dZxbT8VDmzbWVVGSEtn3dZjLzqoXsIyvqqrN09JSZBaCqF6vqKYP8/KRUMkdDY228Oja0AKyzgPotACMF4JBxWlWR4TNvPgWA/UZfqkIWkOHMkdyv+4zcQC57AmeESROqaWs3VgAeFkBPmVkARxsFBWDkHgH7KlkPJQf2Kbb1VdGGKR1GZnVvLk9FRsgY5g8WLFYra854z4OElgZrBWAmqkBdVZaONMUAROQtIrIJOA/4hYj8ymMcxVh/obp6c+TySl1VhYk8gCZjJeeVBpp8pnYWgJoGgKFfmVtlrRXmRWNl3tJQbeoCst4PAKJMoFRZAKp6h6rOUNVqVZ2iqq/3GEcx9VUVZMTOPZJkcCRfZAuslVzeoRAMoL46tgCMvlQ9fXlT/z8UufOsrTlTadBi7AJSMG8FUVeVZU9nL+3G1xKCC6hAJiM01Vayfb9NylnyxU0mZQsaaysRge1GaXUefmMosgCMzOreXN60DQRAc12kAKxSJL161bQ0VLN9X49ZsNslBlAd3a+v/xf7sqigAIqYN6XBrII0sTQsLYDKbIbZk+p59kWbqkMvv7G1BdCby5u7gGZPqiebEcOKZ/uMLogUQC6v7OqwUXT5vP05Jt+TLXvs0l0T7JafRwELpzXyw0c38IW7nyEj0eQ869h6VmzeTV1VBSJRH/YTW+p5dN1OGmoqOX1GM63rdtLVl6OmIku2yBXQ0Z0jr0ptZfR8Z0+O3lzUa+TeZ6OahsSUtzzH37+wg3+8axUiRMFLEWrjwGlTbSVTG2tYsXkPvbk8dVUV1FZmece5x/OjRzeyYEoDyzftpi+ndPflqK3MkomPcdqMJh5cvZ2aiiznzJ7IT5ZvATyCwNFtfWvrRrr7crR39VFbmaUnl2f9jg5OOLaOptpKNuzsoKs3Tz6v1MVKo/gY05treXzjLuqqKqiuyDBvSgOPrN1BbWWWymyGM45v5pG1O7m1dRMzjqkdbCglo6Yyy9yWCdz11FZ6cpELqqYiahA3f2oDnT19bNrViYgwb/IE+vJ5thZNMEOdN0BdZZY5LRN4fMNuAE6b0cS3H4wqq81dQHEtwBfvfoY3nDqNFZv3cMr0Rtbv6KCjJ0dnT45FxzWyY38PL+7pYt6UCXT15grnXlOZYXpzbeG5mRPrqMgKz2xtLyjtKU01tEyoZvnG3azcutf8Wm7Y2VF4/LlfrKSxppKzTziGh9bu5KyZzSzfuJuzZh7DhfPHPg0+KIAilixo4cetG/mP+14wk9lUa3sJLj55Cvc+s43v/WH9EeXJ//eyTazcOjLLwboFdUtDNbOOrePB1dtZ+uyBxYMZKU2mx5kzjxn7gx6C1y+awjfuX8t3/7COLqPNYayV+cJpjUyaUMXtj2/mx8s2mcicNaneRE7ClefO5NbW6Ny+9cDaQe/PhuoKVnx67EOlwQVUxJIFk7nt2leYyrS2AN585nSe/odLWPWZS6irOnj1NxQjnfzBvtNhTWWWpf/71Xzlj8846LVrl8wdc3lvOHUq/3blmWN+3EPxv163gFWfuYRnPnOpmUxrd96sSfW0/u1r+eCrx/66DcUNl55kJguixcO6L1zGui9cxpvPmD7oe9q7+0pSLBYUwABObJlgKq/BWAEUM6WxpqTHX7IgMlkt0/iKWXhc40HP/dHZM8ZcTnNd1Zgfc7zitYHVwmkHX8vRkLiWBsNzl67h7qVSxHuCC2gAldkMn7liEfOnNLBq616e27aPU6c38fCaHUBU9l9fVcG5sycW3Au1VVkumDuJe5/ddsD66JzZE1kwpYHvPbQegFOnN/HyOcfywOrtvHrBZH7zzEsF37sH37j6bH7x5ItMqKlgxabdQOwbVmXmxDrmtEzgkbU76O7LIxLlu1dkhMpshvrqLOfOnsh98WfQm1eqspnC55DNCH998XzuPH4zf3TW2E+6h8PsY+v58wtm01Rbyb6ePqorssyeVM9HXjOPVVv3Ul+VZebEOo6pr2L5xt0HXLvuvjxNtZWcObOZP7ywg544HvKy2RN5cPX2qP+PQHU2w3Wvne9yfsXc8hcv49ZHN3LWCcewpm0/W/d0cs6siezvzvHUlj0I0X2anOPMY+tprq3kyfi6F+9P3d2XRzWaJE+a1sDjGyIf9GMbdnHK9Cb7kwMumDeJt589g9OOb+apTXvY29VLVUWGc2dPZNXWvWxv7+G8E49l3Y79bNkdnXtHT441bfvY35Nj3uQJNNdV0rpuFzMn1nH1ebP4UesGpjbW8ODqHRw7oYpFxzUx3dj/P5CPvGYuezp76erNccG8SbSu28WJk+tZvmE32RLkp4r1LlijYfHixdra2uo9jEAgEDiqEJFlqnrQ3ivBBRQIBAIpJSiAQCAQSClBAQQCgUBKCQogEAgEUkpQAIFAIJBSggIIBAKBlBIUQCAQCKSUoAACgUAgpRxVhWAi0gasH+G/TwK2j+FwPAnnMj4pl3Mpl/OAcC4JJ6jqQe1EjyoFMBpEpHWwSrijkXAu45NyOZdyOQ8I53IoggsoEAgEUkpQAIFAIJBS0qQAbvIewBgSzmV8Ui7nUi7nAeFchiU1MYBAIBAIHEiaLIBAIBAIFBEUQCAQCKSU1CkAEfmwiDwjIk+LyJe8xzNaROQ6EVERmeQ9lpEiIl+Or8mTInKHiDR7j+lIEJFLRORZEVktItd7j2ekiMjxInKviKyMvx8f9R7TaBGRrIg8LiI/9x7LaBCRZhH57/h7skpEzhuL46ZKAYjIq4ErgNNVdRHwT85DGhUicjzwOmCD91hGyT3AKap6GvAccIPzeA4bEckCNwKXAguBK0Vkoe+oRkwfcJ2qLgReDnzwKD6XhI8Cq7wHMQZ8Ffilqp4EnM4YnVOqFADwAeALqtoNoKrbnMczWv4F+BuiLV2PWlT1f1S1L/7zIcBnE+GRcS6wWlXXqGoP8EOiRcZRh6puVdXH4sftRJPMdN9RjRwRmQFcBnzTeyyjQUSagAuBbwGoao+q7h6LY6dNAcwHXikiD4vIfSJyjveARoqIXAFsVtUnvMcyxvwZcLf3II6A6cDGor83cRRPmgkiMgs4E3jYeSij4V+JFkh553GMltlAG/Cd2J31TRGpH4sDV4zFQcYTIvJrYOogL32S6HwnEpm35wC3isgcHae5sIc4l08QuX+OCoY7F1X9SfyeTxK5IW62HFvgQERkAnAb8Fequtd7PCNBRN4IbFPVZSKyxHk4o6UCOAv4sKo+LCJfBa4H/m4sDlxWqOrFQ70mIh8Abo8n/EdEJE/UYKnNanxHwlDnIiKnEq0KnhARiFwmj4nIuar6ouEQD5vhrguAiLwXeCPwmvGqkIdgM3B80d8z4ueOSkSkkmjyv1lVb/cezyg4H7hcRN4A1ACNIvJ9VX2387hGwiZgk6om1th/EymAUZM2F9CdwKsBRGQ+UMVR2ClQVVeo6mRVnaWqs4hukLPG6+R/KETkEiJT/XJV7fAezxHyKDBPRGaLSBXwDuCnzmMaERKtJr4FrFLVr3iPZzSo6g2qOiP+frwD+O1ROvkTf683isiC+KnXACvH4thlZwEcgm8D3xaRp4Ae4D1H2WqzXPk6UA3cE1s0D6nq+32HdHioap+IfAj4FZAFvq2qTzsPa6ScD1wFrBCR5fFzn1DVu/yGFIj5MHBzvMhYA/zpWBw0tIIIBAKBlJI2F1AgEAgEYoICCAQCgZQSFEAgEAiklKAAAoFAIKUEBRAIBAIpJSiAQGoQkWNFZHn886KIbI4f7xORfy+RzL8SkatH8H9VIvI7EUlbqnbAkJAGGkglIvIpYJ+qlqwjbDx5P0ZUpNd3qPcP8v9/T9RoLrTGCJSEYAEEUo+ILEn6xYvIp0Tkv0TkfhFZLyJvFZEvicgKEfll3CoBETk7bii4TER+JSLTBjn0RcBjyeQvIktFZHH8eJKIrIsfLxKRR2Jr5EkRmRf//53Au0p79oE0ExRAIHAwJxJN3pcD3wfuVdVTgU7gslgJ/BvwNlU9m6jC/HODHOd8YNlhyHs/8FVVPQNYTNTaA+ApoqaFgUBJCP7FQOBg7lbVXhFZQdTe4Zfx8yuAWcAC4BT6W1dkga2DHGcah7dxxx+AT8b9629X1ecBVDUnIj0i0hD35w8ExpSgAAKBg0k2DMqLSG9Rv6g80XdGgKdV9VDb8nUSdaIsRuLflckTqnqLiDxMtHnJXSLyl6r62/jlaqBr5KcSCAxNcAEFAkfOs0BLsi+riFSKyKJB3rcKmDvgucSls4TIckBE5gBrVPVrwE+A0+LnjwW2q2rvmJ9BIEBQAIHAERNv/fg24Isi8gSwHHjFIG+9m2grv2IuFpFHgYuBnSLyEeCPgafiDpynAN+N3/tq4BdjfgKBQExIAw0ESoiI3AH8jao+LyJLgY+pauth/u/twPWq+lwpxxhIL8ECCARKy/VEweAjIu77fmeY/AOlJFgAgUAgkFKCBRAIBAIpJSiAQCAQSClBAQQCgUBKCQogEAgEUkpQAIFAIJBS/j8OYN94rnc1JwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "csv_filename = \"https://github.com/scottprahl/RigolWFM/raw/master/wfm/DS1102E-B.csv\"\n",
    "\n",
    "my_data = np.genfromtxt(csv_filename, delimiter=',', skip_header=2).T\n",
    "\n",
    "plt.plot(my_data[0]*1e6, my_data[1])\n",
    "plt.xlabel(\"Time (µs)\")\n",
    "plt.ylabel(\"Volts (V)\")\n",
    "plt.title(\"DS1102E-B with a single trace\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now for the `wfm` data\n",
    "\n",
    "First let's have look at the description of the internal file structure. We see that only channel 1 has been enabled."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "downloading 'https://github.com/scottprahl/RigolWFM/raw/master/wfm/DS1102E-B.wfm?raw=true'\n",
      "    General:\n",
      "        File Model   = wfm1000e\n",
      "        User Model   = DS1102E\n",
      "        Parser Model = wfm1000e\n",
      "        Firmware     = unknown\n",
      "        Filename     = DS1102E-B.wfm\n",
      "        Channels     = [1]\n",
      "\n",
      "     Channel 1:\n",
      "         Coupling =  unknown\n",
      "            Scale =     2.00  V/div\n",
      "           Offset =     0.00  V\n",
      "            Probe =       1X\n",
      "         Inverted =    False\n",
      "\n",
      "        Time Base =    1.000 µs/div\n",
      "           Offset =    0.000  s\n",
      "            Delta =   10.000 ns/point\n",
      "           Points =    16380\n",
      "\n",
      "         Count    = [        1,        2,        3  ...     16379,    16380]\n",
      "           Raw    = [      142,      141,      141  ...        70,       70]\n",
      "           Times  = [-81.900 µs,-81.890 µs,-81.880 µs  ... 81.890 µs,81.900 µs]\n",
      "           Volts  = [ -1.20  V, -1.12  V, -1.12  V  ...   4.56  V,  4.56  V]\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# raw=true is needed because this is a binary file\n",
    "wfm_url = \"https://github.com/scottprahl/RigolWFM/raw/master/wfm/DS1102E-B.wfm\" + \"?raw=true\"  \n",
    "w = rigol.Wfm.from_url(wfm_url, 'DS1102E')\n",
    "description = w.describe()\n",
    "print(description)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "w.plot()\n",
    "plt.xlim(-6,6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DS1102E-E\n",
    "\n",
    "[Contributed by @Stapelberg](https://github.com/scottprahl/RigolWFM/issues/11#issue-718562669)\n",
    "\n",
    "This file uses a 10X probe.  First let's have look at the description of the internal file structure. We see that only channel 1 has been enabled and it has a 10X probe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "downloading 'https://github.com/scottprahl/RigolWFM/raw/master/wfm/DS1102E-E.wfm?raw=true'\n",
      "    General:\n",
      "        File Model   = wfm1000e\n",
      "        User Model   = DS1102E\n",
      "        Parser Model = wfm1000e\n",
      "        Firmware     = unknown\n",
      "        Filename     = DS1102E-E.wfm\n",
      "        Channels     = [1]\n",
      "\n",
      "     Channel 1:\n",
      "         Coupling =  unknown\n",
      "            Scale =    10.00  V/div\n",
      "           Offset =   -30.80  V\n",
      "            Probe =      10X\n",
      "         Inverted =    False\n",
      "\n",
      "        Time Base =    5.000 ms/div\n",
      "           Offset =   12.800 ms\n",
      "            Delta =  200.000 ns/point\n",
      "           Points =  1048572\n",
      "\n",
      "         Count    = [        1,        2,        3  ...   1048571,  1048572]\n",
      "           Raw    = [      132,      132,      132  ...       134,      134]\n",
      "           Times  = [-92.057 ms,-92.057 ms,-92.057 ms  ... 117.657 ms,117.657 ms]\n",
      "           Volts  = [ 28.80  V, 28.80  V, 28.80  V  ...  28.00  V, 28.00  V]\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# raw=true is needed because this is a binary file\n",
    "wfm_url = \"https://github.com/scottprahl/RigolWFM/raw/master/wfm/DS1102E-E.wfm\" + \"?raw=true\"  \n",
    "w = rigol.Wfm.from_url(wfm_url, 'DS1102E')\n",
    "description = w.describe()\n",
    "print(description)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "w.plot()\n",
    "#plt.xlim(-6,6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernel_info": {
   "name": "python3"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
  },
  "nteract": {
   "version": "0.15.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
